Patent Publication Number: US-2015066650-A1

Title: Method and Apparatus for Advertisements in Mobile Content Distribution Systems

Description:
BACKGROUND 
     Service providers and device manufacturers (e.g., wireless, cellular, etc.) are continually challenged to deliver value and convenience to consumers by, for example, providing compelling internet services. One area of interest has been the development of distributing content via peer-to-peer (P2P) systems. These systems using, for example, Bluetooth, may provide content item sharing without the need for an Internet connection, thus permitting sharing even with little Internet infrastructure. However, content distributed via such offline sharing often lacks monetized business model, more precisely, presenting advertisements tailored to target audiences. Accordingly, advertisement providers face technical challenges in reaching target users who receive content via offline, P2P systems. 
     Some Example Embodiments 
     Therefore, there is a need for an approach for pairing advertisements to content items using distribution characteristics. 
     According to one embodiment, a method comprises determining one or more distribution characteristics of one or more first content items that are distributed among one or more devices. The method also comprises processing and/or facilitating a processing of the one or more distribution characteristics to cause, at least in part, a selection of one or more second content items. The method further comprises processing and/or facilitating a processing of the one or more first content items to cause, at least in part, an embedding of the one or more second content items in the one or more first content items. 
     According to another embodiment, an apparatus comprises at least one processor, and at least one memory including computer program code for one or more computer programs, the at least one memory and the computer program code configured to, with the at least one processor, cause, at least in part, the apparatus to determine one or more distribution characteristics of one or more first content items that are distributed among one or more devices. The apparatus is also caused to process and/or facilitate a processing of the one or more distribution characteristics to cause, at least in part, a selection of one or more second content items. The apparatus is further caused to process and/or facilitate a processing of the one or more first content items to cause, at least in part, an embedding of the one or more second content items in the one or more first content items. 
     According to another embodiment, a computer-readable storage medium carries one or more sequences of one or more instructions which, when executed by one or more processors, cause, at least in part, an apparatus to determine one or more distribution characteristics of one or more first content items that are distributed among one or more devices. The apparatus is also caused to process and/or facilitate a processing of the one or more distribution characteristics to cause, at least in part, a selection of one or more second content items. The apparatus is further caused to process and/or facilitate a processing of the one or more first content items to cause, at least in part, an embedding of the one or more second content items in the one or more first content items. 
     According to another embodiment, an apparatus comprises means for determining one or more distribution characteristics of one or more first content items that are distributed among one or more devices. The apparatus also comprises means for processing and/or facilitating a processing of the one or more distribution characteristics to cause, at least in part, a selection of one or more second content items. The apparatus further comprises means for processing and/or facilitating a processing of the one or more first content items to cause, at least in part, an embedding of the one or more second content items in the one or more first content items. 
     In addition, for various example embodiments of the invention, the following is applicable: a method comprising facilitating a processing of and/or processing (1) data and/or (2) information and/or (3) at least one signal, the (1) data and/or (2) information and/or (3) at least one signal based, at least in part, on (or derived at least in part from) any one or any combination of methods (or processes) disclosed in this application as relevant to any embodiment of the invention. 
     For various example embodiments of the invention, the following is also applicable: a method comprising facilitating access to at least one interface configured to allow access to at least one service, the at least one service configured to perform any one or any combination of network or service provider methods (or processes) disclosed in this application. 
     For various example embodiments of the invention, the following is also applicable: a method comprising facilitating creating and/or facilitating modifying (1) at least one device user interface element and/or (2) at least one device user interface functionality, the (1) at least one device user interface element and/or (2) at least one device user interface functionality based, at least in part, on data and/or information resulting from one or any combination of methods or processes disclosed in this application as relevant to any embodiment of the invention, and/or at least one signal resulting from one or any combination of methods (or processes) disclosed in this application as relevant to any embodiment of the invention. 
     For various example embodiments of the invention, the following is also applicable: a method comprising creating and/or modifying (1) at least one device user interface element and/or (2) at least one device user interface functionality, the (1) at least one device user interface element and/or (2) at least one device user interface functionality based at least in part on data and/or information resulting from one or any combination of methods (or processes) disclosed in this application as relevant to any embodiment of the invention, and/or at least one signal resulting from one or any combination of methods (or processes) disclosed in this application as relevant to any embodiment of the invention. 
     In various example embodiments, the methods (or processes) can be accomplished on the service provider side or on the mobile device side or in any shared way between service provider and mobile device with actions being performed on both sides. 
     For various example embodiments, the following is applicable: An apparatus comprising means for performing the method of any of originally filed claims  1 - 20  and  36 - 48 . 
     Still other aspects, features, and advantages of the invention are readily apparent from the following detailed description, simply by illustrating a number of particular embodiments and implementations, including the best mode contemplated for carrying out the invention. The invention is also capable of other and different embodiments, and its several details can be modified in various obvious respects, all without departing from the spirit and scope of the invention. Accordingly, the drawings and description are to be regarded as illustrative in nature, and not as restrictive. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       The embodiments of the invention are illustrated by way of example, and not by way of limitation, in the figures of the accompanying drawings: 
         FIG. 1  is a diagram of a system capable of pairing advertisements to content items using distribution characteristics, according to one embodiment; 
         FIG. 2  is a diagram of the components of a distribution processor, according to one embodiment; 
         FIG. 3  is a diagram of the components of an accessibility platform, according to one embodiment; 
         FIG. 4  is a flowchart of a process for pairing advertisements to content items using distribution characteristics, according to one embodiment; 
         FIG. 5  is a flowchart of a process for determining distribution characteristics of one or more content items, according to one embodiment; 
         FIG. 6  is a diagram of a scenario for updating advertisement-content item pairings, according to one embodiment; 
         FIGS. 7A-7E  are diagrams of calculations for determining distribution characteristics utilized in the processes of  FIGS. 4 and 5 , according to various embodiments; 
         FIG. 8  is a diagram of hardware that can be used to implement an embodiment of the invention; 
         FIG. 9  is a diagram of a chip set that can be used to implement an embodiment of the invention; and 
         FIG. 10  is a diagram of a mobile terminal (e.g., handset) that can be used to implement an embodiment of the invention. 
     
    
    
     DESCRIPTION OF SOME EMBODIMENTS 
     Examples of a method, apparatus, and computer program for pairing advertisements to content items using distribution characteristics are disclosed. In the following description, for the purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of the embodiments of the invention. It is apparent, however, to one skilled in the art that the embodiments of the invention may be practiced without these specific details or with an equivalent arrangement. In other instances, well-known structures and devices are shown in block diagram form in order to avoid unnecessarily obscuring the embodiments of the invention. 
       FIG. 1  is a diagram of a system capable of pairing one or more first content items to one or more second content items using distribution characteristics. In one embodiment, this could include pairing one or more content items to one or more advertisements using distribution characteristics. As discussed, content distributed via offline sharing often lacks advertisements or advertisements tailored to target audiences. Accordingly, device manufacturers and service providers face technical challenges in enabling their advertisements to reach target users who receive content via offline, P2P systems. The one or more content items may be, for example, an audio file, video file, song, picture, presentation, Internet web page, Internet link, document, database, book, map, point of interest, application, applet, computer program, service guide, or any combination thereof. The one or more advertisements may be, for example, an audio file, video file, song, picture, presentation, Internet web page, Internet link, document, database, book, map, point of interest, application, applet, computer program, service guide, or any combination thereof. 
     To address this problem, a system  100  of  FIG. 1  introduces the capability to pair advertisements to content items using distribution characteristics. The system  100  may, for instance, enable advertisements to be distributed along with content items based on distribution characteristics of the content items. As shown in  FIG. 1 , the system  100  comprises a user equipment (UE)  101  (or UE  101   a - 101   n ) having connectivity to respective profile platforms  103 , as well as a distribution processor  105 , content providers  107  (or content providers  107   a - 107   k ), and advertisement providers  109  (or advertisement providers  109   a - 109   m ) via a communication network  111 . The UEs  101  may include or have access to a profile platform  103  (or profile platform  103   a - 103   n ) to enable the UEs  101  to interact with the distribution processor  105 , one or more content providers  107 , one or more advertisement providers  109 , and communication network  111 . Profile platforms  103  may have access to user profiles associated with respective UEs  101 . User profiles may include basic information about a user associated with one or more UEs  101   a - 101   n , such as, gender, age, language, etc. User profiles may be generated in a variety of ways, including directly prompting users to provide information, obtaining user context information, integrating content of the profile platforms  103   a - n , or some combination thereof. 
     In one embodiment, the system  100  may include a server and many clients (peers). In system  100 , for instance, the distribution processor  105  may represent the server and the UEs  101  may represent the clients. In some embodiments, each of the UEs  101  may communicate with the distribution processor  105  through communication network  111 , which may include online means (e.g., short message service (SMS), General Packet Radio Service (GPRS), etc.). Additionally, or alternatively, the UEs  101  may communicate with each other through communication network  111 , which may include offline means (e.g. Bluetooth or other short-range wireless networks). 
     Meanwhile, content providers  107  may upload content items (and/or metadata pertaining to the content items) to the distribution processor  105  (e.g., with advertisements already embedded in the content items, without the advertisements embedded in the content items, etc.). In one scenario, clients may download songs (e.g., uploaded by musicians) directly from the server and/or from other clients. Advertisement providers  109  may also upload their advertisements (and/or metadata pertaining to the advertisements) to the distribution processor  105 . The distribution processor  105  may then process the input from UEs  101 , content providers  107 , and advertisement providers  109  to output content item-advertisement pairings. In one embodiment, UEs  101  provide associated user profile information, content providers  107  submit content item distribution information, and advertisement providers  109  give target audience specifications to the distribution processor  105 . The distribution processor  105  then creates, at least in part, content item-advertisement pairings with this information. 
     In some embodiments, an advertisement may be embedded in the content item as metadata, where UEs  101  may, for instance, require an application to interpret the metadata. In other embodiments, an advertisement may be of the same media as the content item, so that a separate application would not be necessary to interpret the advertisement. That is, the application utilized to process the content item may also process the advertisement. 
     In one scenario, an advertisement may be a picture, while a content item may be a song. A UE  101  may, for instance, display the advertisement picture on the user interface of the UE  101  while the song is playing. In another scenario, an advertisement may include an overlay on a content item, such as a picture overlay on a video content item, for instance. In yet another possible scenario, the advertisement may be of the same media as the content item. In this case, the UE  101  may play a paired advertisement preceding the downloaded content item. It is noted that, in certain embodiments, the system  100  may pair one or more advertisements to one or more content items regardless of whether the content item was previously paired with an advertisement. 
     For example, there may be a content item-advertisement relationship where one content item may embed, at most, one advertisement, as determined by distribution processor  105 . To update the pairing relationships of content items and advertisements, the distribution processor  105  may, for instance, embed an advertisement in a content item previously without an embedded advertisement, remove an embedded advertisement from a content item where it was previously embedded, and/or change the advertisement embedded in a content item. As such, advertisements may stay current and the advertisement service (such as the advertisement providers  109 ) may continue to make money as new advertisements occupy advertising slots. In addition, updating the advertisement embedded in a content item may permit the system  100  to gather more input on the content item-advertisement relationship based on the content item distribution characteristics, thus providing the system with increasingly optimized pairings of advertisements to content items. Therefore, updates of the content item-advertisement relationship may occur when a new advertisement arrives, an old advertisement is expiring, when a significant amount of new data on content distribution characteristics have been gathered, etc. 
     By way of example, the communication network  111  of system  100  includes one or more networks such as a data network, a wireless network, a telephony network, or any combination thereof. It is contemplated that the data network may be any local area network (LAN), metropolitan area network (MAN), wide area network (WAN), a public data network (e.g., the Internet), short range wireless network, or any other suitable packet-switched network, such as a commercially owned, proprietary packet-switched network, e.g., a proprietary cable or fiber-optic network, and the like, or any combination thereof. In addition, the wireless network may be, for example, a cellular network and may employ various technologies including enhanced data rates for global evolution (EDGE), general packet radio service (GPRS), global system for mobile communications (GSM), Internet protocol multimedia subsystem (IMS), universal mobile telecommunications system (UMTS), etc., as well as any other suitable wireless medium, e.g., worldwide interoperability for microwave access (WiMAX), Long Term Evolution (LTE) networks, code division multiple access (CDMA), wideband code division multiple access (WCDMA), wireless fidelity (WiFi), wireless LAN (WLAN), Bluetooth®, Internet Protocol (IP) data casting, satellite, mobile ad-hoc network (MANET), near field communication (NFC), and the like, or any combination thereof. 
     The UE  101  is any type of mobile terminal, fixed terminal, or portable terminal including a mobile handset, station, unit, device, multimedia computer, multimedia tablet, Internet node, communicator, desktop computer, laptop computer, notebook computer, netbook computer, tablet computer, personal communication system (PCS) device, personal navigation device, personal digital assistants (PDAs), audio/video player, digital camera/camcorder, positioning device, television receiver, radio broadcast receiver, electronic book device, game device, or any combination thereof, including the accessories and peripherals of these devices, or any combination thereof. It is also contemplated that the UE  101  can support any type of interface to the user (such as “wearable” circuitry, etc.). 
     In one embodiment, the UEs  101  may receive a request from the distribution processor  105 , content providers  107 , advertisement providers  109 , communication network  111 , or any combination thereof, via the communication network  111  to build and transmit associated user profiles from profile platforms  103 . As discussed above, profile platforms  103  may adjust and update user profiles according to user response and input, context information, or any combination thereof. In a further embodiment, content providers  107  may then receive a request from the distribution processor  105  for distribution characteristics regarding content items. In one scenario, the distribution characteristics include distribution history of one or more content items. The distribution processor  105  may also request target audience specifications from advertisement providers  109 . 
     From the user profiles, content distribution history, and target audience specifications submitted through the communication network  111  by the profile platforms  103 , content providers  107 , and advertisement providers  109 , respectively, the distribution processor  105  may determine one or more content item-advertisement relationships. After processing the relationships, the UEs  101 , distribution processor  105 , content providers  107 , and advertisement providers  109 , or any combination thereof; may cause, at least in part, one or more advertisements to be embedded in one or more content items so that the advertisements are distributed in the system along with the content items. 
     In one embodiment, the distribution processor  105  may update embedded advertisements where a content item lacks an advertisement or where previously embedded advertisement(s) are expired. Updates may also be based on increased accuracy of information collected by the profile platforms  103 , distribution processor  105 , content providers  107 , advertisement providers  109 , or some combination thereof, as more information is collected. In this way, system  100  may increase value for advertisement providers  109  in better ensuring that advertisements reach target audiences. 
     By way of example, the UE  101 , profile platforms  103 , distribution processor  105 , content providers  107 , and advertisement providers  109  communicate with each other and other components of the communication network  111  using well known, new or still developing protocols. In this context, a protocol includes a set of rules defining how the network nodes within the communication network  111  interact with each other based on information sent over the communication links. The protocols are effective at different layers of operation within each node, from generating and receiving physical signals of various types, to selecting a link for transferring those signals, to the format of information indicated by those signals, to identifying which software application executing on a computer system sends or receives the information. The conceptually different layers of protocols for exchanging information over a network are described in the Open Systems Interconnection (OSI) Reference Model. 
     Communications between the network nodes are typically effected by exchanging discrete packets of data. Each packet typically comprises (1) header information associated with a particular protocol, and (2) payload information that follows the header information and contains information that may be processed independently of that particular protocol. In some protocols, the packet includes (3) trailer information following the payload and indicating the end of the payload information. The header includes information such as the source of the packet, its destination, the length of the payload, and other properties used by the protocol. Often, the data in the payload for the particular protocol includes a header and payload for a different protocol associated with a different, higher layer of the OSI Reference Model. The header for a particular protocol typically indicates a type for the next protocol contained in its payload. The higher layer protocol is said to be encapsulated in the lower layer protocol. The headers included in a packet traversing multiple heterogeneous networks, such as the Internet, typically include a physical (layer 1) header, a data-link (layer 2) header, an internetwork (layer 3) header and a transport (layer 4) header, and various application (layer 5, layer 6 and layer 7) headers as defined by the OSI Reference Model. 
       FIG. 2  is a diagram of the components of a distribution processor, according to one embodiment. By way of example, the distribution processor  105  includes one or more components, such as software components or modules, for providing advertisement-to-content item pairing using distribution characteristics. It is contemplated that the functions or features of these components may be combined in one or more components or performed by other components of equivalent functionality. In this embodiment, the distribution processor  105  includes control logic  201 , memory  203 , user platform  205 , target platform  207 , accessibility platform  209 , communication interface  211 , and embedding platform  213 . 
     The control logic  201  may, for instance, receive information from the user platform  205 , the target platform  207 , and the accessibility platform  209  to determine an optimal content item-advertisement pairing. The user platform  205  may receive user profile information from various UEs  101  via the profile platforms  103 . The target platform  207  may receive target audience specifications associated with one or more advertisements from advertisement providers  109 . In one embodiment, the target platform  207  may also interact with user platform  205  to provide advertisement providers  109  with statistics of user profiles that have come in contact with a given advertisement. This way, advertisement providers  109  may revise target audience specifications according to distribution characteristics. 
     The accessibility platform  209  may, for example, calculate the likelihood that one or more content items on one or more UEs  101  will be transmitted to one or more other UEs  101 . Then, the control logic  201  may process information received from the user platform  205 , the target platform  207 , and the accessibility platform  209  to select one or more advertisements (e.g., provided by advertisement providers  109 ) to pair with one or more content items (e.g., provided by content providers  107 ). The calculations from the accessibility platform  209  may also help advertisement providers  109  predict users who may see given advertisements and thus permit greater clarity in a target audience. 
     Then, the embedding platform  213  may embed one or more selected advertisements in one or more content items. The embedding platform  213  may embed advertisements in content items previously lacking advertisements or update and replace existing advertisements embedded in content items. The latter may occur when old advertisements expire, new replacement advertisements are generated, or when distribution characteristics indicate another, more suitable advertisement. 
     Additionally, the control logic  201  may also utilize the communication interface  211  to communicate with other components of the UEs  101 , the profile platforms  103 , the distribution processor  105 , the content providers  107 , the advertisement providers  109 , and other components of the system  100 . The communication interface  211  may include multiple means of communication. For example, the communication interface  211  may be able to communicate over SMS, interne protocol, instant messaging, voice sessions (e.g., via a phone network), or other types of communication. 
       FIG. 3  is a diagram of the components of an accessibility platform, according to one embodiment. By way of example, the accessibility platform  209  includes one or more components, such as software components or modules, for providing the distribution characteristics or features that contribute to pairing advertisements to content items. It is contemplated that the functions of these components may be combined in one or more components or performed by other components of equivalent functionality. In this embodiment, the accessibility platform  209  may include a controller  301 , a history module  303 , a graphing module  305 , a probability module  307 , a scoring module  309 , and a sorting module  311 . The components of the accessibility platform  209  may, for instance, determine distribution characteristics by building one or more connection models, such as connection graphs, between users (e.g., of the UEs  101 ), calculating content item to user accessibility, and determining one or more content item-advertisement matching scores. The matching scores may then be used, at least in part, to solve an optimization problem to pair advertisements to content items. 
     In one embodiment, the history module  303  may record and determine content distribution history by determining distribution routes of content items at the server, control logic  201 . This may include recording the UEs  101  that download a given content item. In a further embodiment, history module  303  may upload the recorded metadata to the distribution processor  105  when UEs  101  connect to communication network  111  and distribution processor  105 . For such a scenario, when UEs  101  connect to each other, their respective history modules  303  may exchange their recorded metadata. Analogously, when UEs  101  connect to distribution processor  105  via the communication network  111 , each of the UEs  101  may, for instance, upload all the metadata it has recorded from other UEs  101  to history module  303 . 
     In one embodiment, the graphing module  305  may then build a connection graph based on the content distribution history determined by the history module  303 . To build the connection graph, graphing module  305  may determine the strength of the connections between UEs  101 . For instance, the strength of the connections (or link strength) between UEs  101  may be contingent on the probability of content transmission between two UEs  101 . In other words, two UEs  101  are more strongly connected when there is the high probability of content sharing between the UEs  101 , or, there is content frequently shared between UEs  101 . For example, in defining each UE  101  as a node, node A may have a total of 10 content items. In sharing  3  of those content items with node B, the link from A to B has a strength value of 3/10, or, 0.3. 
     Then, the graphing module  305  may work with the probability module  307  to calculate content-user accessibility, or the probability that a given UE  101  may receive a given content item after several rounds of distribution. To do this, probability module  307  may use probability theory. In one embodiment, the probability module  307  may calculate a k-hop content transmission probability matrix as formulated below: 
         P   (k)   =p   ijk   , i= 1  . . . L, j≠ 1  . . . L, i≠j, k≧ 1 
     With this formula, the probability module  307  may calculate the probability that a content item will be transmitted from the i-th user to the j-th user in exactly k hops. To calculate p ijk  in one embodiment, the probability module  307  may graph all the paths from i to j with length k, then estimate the probability of each path by multiplying all the link strengths in that path according to probability theory: 
         p   ijk ≈1−Π path     m   (1−prob(path m ))
 
     In one further embodiment, the probability module  307  may calculate the accessibility according to the probabilities where content items have already reached nodes (or UEs  101 ), and can thus be further distributed. For example, probability module  307  may calculate the accessibility of user i to content c with the formula: 
     
       
         
           
             
               
                 p 
                 
                   i 
                    
                   
                       
                   
                    
                   c 
                 
               
               = 
               
                 1 
                 - 
                 
                   
                     ∏ 
                     
                       j 
                       ∈ 
                       
                         J 
                          
                         
                           ( 
                           c 
                           ) 
                         
                       
                     
                   
                    
                   
                       
                   
                    
                   
                     
                       ∏ 
                       
                         k 
                         = 
                         
                           1 
                           - 
                           K 
                         
                       
                     
                      
                     
                         
                     
                      
                     
                       ( 
                       
                         1 
                         - 
                         
                           
                              
                             
                               - 
                               ak 
                             
                           
                            
                           
                             p 
                             jik 
                           
                         
                       
                       ) 
                     
                   
                 
               
             
             , 
             
               
                 
                   
                     i 
                     ∉ 
                     
                       J 
                        
                       
                         ( 
                         c 
                         ) 
                       
                     
                   
                   &amp; 
                 
                  
                 
                   p 
                   j 
                 
               
               = 
               1 
             
             , 
             
               j 
               ∈ 
               
                 J 
                  
                 
                   ( 
                   c 
                   ) 
                 
               
             
           
         
       
     
     Where J(c) is the set of nodes that already have c(already reached nodes+distribution processor  105 ), a is a constant to control the decay rate, and K is the maximum number of hops. 
     Additionally, or alternatively, the probability module  307  may calculate the accessibility according to distribution routes of content items, where link strengths are increased as contents are distributed along the routes. For this, the probability module  307  may update link strengths and re-calculate p ijk  with the formula: 
         p   i =1−Π k=1 . . . K (1 −e   −ak   p′   sik )
 
     With this formula, s is the server, or the distribution processor  105 . 
     To take into account the scenario where UEs  101  download only a limited number of content items, the probability module  307  may be modified. For one possible modification, probability module  307  may calculate p ic  as described above, but for each user, say, i 0 , the probability module may sort the accessibility p i0c  in descending order. Then, the probability module  307  may select top k values from p i0c , where k can be a constant, or can be determined based on the number of content items already in the UE  101 . Afterwards, the probability module  307  may set p′ i0c =p i0c  if the latter is within top k values, or p′ i0c =0 if not. Based on these calculations, the new is the accessibility. 
     Once the probability module  307  has calculated accessibility, the controller  301  may cause the scoring module  309  to calculate content item-advertisement matching scores. For each advertisement, respective advertisement providers  109  may define target audience specifications in the form of a user profile, e.g., Female, Age 18-25, Home location in the city of Beijing. From this specification, in one embodiment, the scoring module  309  may pinpoint UEs  101  of targeted users and select these UEs  101 . The scoring module  309  may then calculate a content item-advertisement matching score based on the sum of accessibility of the advertisement&#39;s targeted users to the content item. 
     Following the calculating of content item-advertisement matching scores, sorting module  311  may formulate and solve an optimization problem, optimizing the selection of an advertisement with a corresponding content item. For instance, sorting module  311  may be based on one or more optimization problems formulated according to various advertisement revenue models. In one such scenario, an advertisement provider  109  may pay per download by a UE  101  (either from distribution processor  105 , or from other UEs  101 ) if the downloading user belongs to the target audience. Here, for M contents (indexed by i=1 . . . M) and N ads (indexed by j=1 . . . N), probability module  307  may calculate M*N content item-advertisement matching scores. Then, sorting module  311  may define: 
         b   ij =1 if the  i -th content embeds the  j -th advertisement, otherwise  b   ij =0 
     From there, sorting module  311  may maximize the optimization problem: 
       Σ i Σ j   b   ij   m   ij   c   j , for  i= 1  . . . M, Σ   j   b   ij ≦1
 
     In this case, m ij  is the matching score and c j  is the price of the j-th advertisement. Σ j b ij ≦1 given the constraint that one content item may embed at most one advertisement, but such constraints may be adjusted according to the optimization problem defined in each scenario. The sorting module  311  may then solve the optimization problem to yield the “optimal” b ij , and thus select the optimal advertisement to be paired with a given content item. 
     In another scenario, an optimization problem may be formulated where an advertisement provider  109  may pay per download, but the prices for downloads by target UEs  101  and non-targeted UEs  101  are different. This optimization problem may be: 
       Σ i Σ j   b   ij ( c   j1   m   ij   +c   j2 ( m   i   −m   ij )), for  i= 1  . . . M, Σ   j   b   ij ≦1
 
     c j1  may be the price for download by target UEs  101 , c j2  may be the price for download by non-targeted UEs  101 , and m i  may be the sum of accessibility of all UEs to the i-th content. Again, the sorting module  311  may solve this optimization problem to select an optimal advertisement-content item pairing. 
     Thus far, the formulas are based on the constraint that each content item may embed, at most, one advertisement. However, the embedding platform  213  may embed multiple advertisements in one content item, given some variations in the optimization problem performed by scoring module  309  and sorting module  311 . One possible variation may be formulating the constraint as: 
       Σ j   b   ij   ≦d   i  
 
     where d i  is the capacity of the i-th content, i.e. the maximum number of advertisements that may be embedded. In adjusting the parameters of the optimization problem, changes may be made to the quantity of advertisements embedded in a given content item. 
     The scoring module  309  and sorting module  311  may, for instance, rely on data gathered over time, such as distribution history. As such, as content providers  107  continuously provide new contents, there is the concern that content item-advertisement pairing for new content items may be inferior to that of older content items. This may occur because there is less distribution history for the new content items. One possible solution is to divide the content items by “old” or “new.” For the newer content items, the controller  301  may discern “similarities” between the newer content item and older content items. One example may include song content items that were composed by the same musician or song content items that are of the same genre, etc. Then, for each advertisement, the scoring module may calculate an average content item-advertisement matching score of “similar” older content items. The matching score of the content item itself and the matching scope of “similar” older contents may then be combined to project an optimal advertisement pairing for the new content item. The assumption is that new content items will fall into distribution routes that reflect distribution routes of the older content items they resemble. Based on this assumption, the advertisement pairings for new content items may quickly become relevant or optimized, despite lacking more distribution information. 
       FIG. 4  is a flowchart of a process for pairing advertisements to content items using distribution characteristics for content item distribution, according to one embodiment. In one embodiment, the distribution processor  105  performs the process  400  and is implemented in, for instance, a chip set including a processor and a memory as shown in  FIG. 9 . In step  401 , the distribution processor  105  may determine one or more distribution characteristics of one or more first content items that are distributed among one or more devices (UEs  101 ). In one embodiment, distribution characteristics may relate to content distribution history or the distribution routes of different contents. For step  403 , the distribution processor  105  may process and/or facilitate a processing of the one or more distribution characteristics to cause, at least in part, a selection of one or more second content items. As previously discussed, the one or more second content items may include one or more advertisements. 
     In one embodiment, step  403  may further comprise of determining user profile information associated with the one or more devices, wherein the selection of the one or more second content items is further based, at least in part, on the user profile information. For this, the user platform  205  may aggregate and supply the control logic  201  with user profile information associated with the one or more devices. In one instance, such user profile information may be provided by the profile platforms  103  of UEs  101 , either via request, context information, or any combination thereof. 
     Then, in step  405 , the distribution processor  105  may determine one or more target audience specifications associated with the one or more second content items, wherein the selection of the one or more second content items is further based, at least in part, on the one or more target audience specifications. In one scenario, advertisement target audience specifications may be provided by advertisement providers  109 . 
     For the steps that follow, the distribution processor  105  may process and/or facilitate a processing of the one or more first content items to cause, at least in part, an embedding of the one or more second content items in the one or more first content items. In step  407 , the control logic  201  may evaluate how closely target audience specifications (e.g., as provided by advertisement providers  109 ) align with content item distribution characteristics. In other words, for step  407 , the control logic  201  may, for instance, evaluate whether an advertisement will suit the user downloading a content item, based on distribution characteristics associated with the content item. If an advertisement is found suitable, the embedding platform  213  may embed the advertisement in the content item (steps  409  and  411 ). If not, the accessibility platform  209  may compare another set of advertisement target audience specifications (for another advertisement) to content item distribution characteristics to find a suitable pairing. In one embodiment, the embedding platform  213  may cause, at least in part, a distribution of the one or more first content items with the embedded one or more second content items among the one or more devices via at least one peer-to-peer mechanism. 
     In one further embodiment, process  400  may include the control logic  201  determining one or more updates to the one or more distribution characteristics, the user profile information, the one or more second content items, the one or more target audience specifications, or a combination thereof, and causing, at least in part, a re-determination of the selection of the one or more second content items based, at least in part, on the one or more updates. For instance, a content item-advertisement relationship may not be consistent throughout an entire system immediately when a server updates a content item-advertisement relationship. An update mechanism could correct such inconsistency wherein new content item-advertisement relationships could replace existing or absent content item-advertisement relationships when UEs  101  connect to the distribution processor  105  or when UEs  101  connect to one another. In one scenario, when UE  101  connects to the distribution processor  105 , the distribution processor  105  may embed advertisements into the content item. In an alternate scenario, this same synchronization of advertisements may occur when two UEs  101  connect with one another. The same process may occur whether or not the content item previously had an advertisement embedded in it. 
       FIG. 5  is a flowchart of a process for determining distribution characteristics of one or more content items, according to one embodiment. In one embodiment, the distribution processor  105  performs the process  500  and is implemented in, for instance, a chip set including a processor and a memory as shown in  FIG. 9 . As stated previously, the distribution processor  105  may determine one or more distribution characteristics of one or more content items that are distributed among one or more devices. In step  501 , the distribution processor  105  may determine one or more distribution routes of the one or more first content items among the one or more devices, wherein the one or more distribution characteristics include, at least in part, the one or more distribution routes. To do this, the distribution processor  105  may, for instance, determine the different distribution routes taken by various content items from servers to UEs  101  and/or between UEs  101 . 
     Then, at step  503 , the distribution processor  105  may determine one or more probabilities that a first one of the one or more devices will distribute the one or more first content items to at least a second one of the one or more devices. In one embodiment, the distribution processor  105  cause, at least in part, a creation of one or more connection models among the one or more devices based, at least in part on the one or more probabilities, wherein the one or more distribution characteristics include, at least in part, the one or more connection models (step  505 ). In one scenario, the distribution processor  105  may determine a number of hops for distributing the one or more first content items from a first one of the one or more devices to at least a second one of the one or more devices, and determine the one or more probabilities based, at least in part, on the number of hops. 
     Based on the above calculations, the distribution processor  105  may determine an accessibility of the one or more first content items to the one or more devices based, at least in part, on the one or more probabilities, the one or more connection models, the number of hops, or a combination thereof; wherein the one or more distribution characteristics include, at least in part, the accessibility (step  507 ). The distribution processor  105  may then score content item-advertisement matches according to accessibility to cause, at least in part, a sorting of the one or more first content items based, at least in part on the accessibility, wherein the selection of the one or more second content items is further based, at least in part, on the sorting (step  509 ). As discussed above, the distribution processor  105  may use various optimization problems to perform the sorting, depending on the optimal pairing defined, at least in part, by advertisement providers  109 . 
       FIG. 6  illustrates an example of the advertisement update process wherein advertisements are synchronized when UE  101  connects to a server (such as distribution processor  105 ), and again, when UE  101  connects to another UE  101 . For instance, in one embodiment, as of time  601 , content item 1 is left without any advertisement embedded in it (e.g. a previously embedded advertisement 1 may have expired). At time  603 , embedding platform  213  embeds advertisement 2 in content item 1. Thus, when Client 1 (e.g., UE  101 ) connects to server distribution processor  105  at time  605 , Client 1&#39;s previously downloaded content 1 is updated to include advertisement 2. Synchronization is further performed at time  607  between UEs  101  when Client 1 and Client 2 connect, and content 1 is updated and/or transmitted to Client 2 containing the embedded advertisement 2. 
       FIGS. 7A-7E  are illustrations of the processes of  FIG. 5 , according to various embodiments.  FIG. 7A  shows the building of user profiles, wherein each point (e.g., points  701  and  703 ) represents a UE  101 , or end user. By way of example, the profile platforms  103  may contain user profiles associated with respective UEs  101 . In one embodiment, user profiles may include basic information regarding a user associated with the one or more UEs  101   a - 101   n , for example, gender, age, language, etc. In one scenario, the profile platforms  103  may directly prompt users to provide the information to build their user profiles. In another scenario, profile platforms  103  may record user context and build user profiles that include information such as user location, interests, preferences, etc. Profile platforms  103  may also use a combination of user responses and context information to build user profiles. One such user profile may be: male, 24, English; home location (GPS) 35°N, 120°E; musical interest: Pop, R&amp;B, as shown by point  701 . Another such user profile may be as shown by point  703 : Female, 20, French; home location (GPS) 36°N, 120°E; musical interest: R&amp;B, Jazz. 
     In  FIG. 7B , the history module  303  may determine one or more distribution characteristics of one or more content items distributed among the UEs  101 . One distribution characteristic may include distribution history in the form of distribution routes. For example, in  FIG. 7B , when UE  101   c  receives a given content item 1 from UE  101   b , history module  303  may record, “content item 1: from server-&gt;UE  101   a -&gt;UE  101   b .” Likewise, when UE  101   e  receives content item 1 from UE  101   c , it may receive the metadata, “content item 1: from server-&gt;UE  101   a -&gt;UE  101   b -&gt;UE  101   c ,” as seen from route  705   a . Route  705   b  illustrates another example route, possibly of a different content item. As previously discussed, history module  303  may then cause an upload of such recorded distribution characteristics to the distribution processor  105  such that the recorded distribution characteristics are exchanged among the UEs  101  that are connected to distribution processor  105 . 
       FIG. 7C  gives a possible embodiment where the graphing module  305  starts to create one or more connection graphs among the one or more UEs  101  based on the one or more distribution characteristics. The graphing module  305  may build such a connection graph based on the number of shared items versus total items, between one or more UEs  101 . For instance, if the UE  101   h  has a total of 10 content items and shares  5  of these content items with the UE  101   i , their link strength  707  is 0.5. Connection graphs may thus show stronger or weaker link strengths between UEs  101  that frequently share content items, therefore implying a corresponding probability of content sharing and transmission between the UEs  101 . 
     Next,  FIG. 7D  displays a possible distribution route  709 , following the calculations of the graphing module  305  and probability module  307 . The probability module  307  may calculate the possible distribution route may be based on the connection graphs and probability theory, as described earlier. Calculations by the probability module  307  may predict the probability that a given content item may be transferred to a given UE  101 . 
       FIG. 7E  shows the determination of one or more target audience specifications associated with the one or more advertisements, which scoring module  309  and sorting module  311  may then use in conjunction with distribution characteristics found by the history module  303 , graphing module  305 , and probability module  307  to select an optimal advertisement for embedding. Based on the specifications, the scoring module  309  may distinguish UEs  101  that fit the target audience specifications  711 , over UEs  101  that do not fit target audience specifications  711 . Scoring module  309  may then assess the accessibility of a given advertisement&#39;s targeted users  713  to yield a content item-advertisement matching score. With the content item-advertisement matching score, the sorting module  311  may better select one or more suitable advertisements to be paired with a given content item. 
     The processes described herein for pairing advertisements to content items using distribution characteristics may be advantageously implemented via software, hardware, firmware or a combination of software and/or firmware and/or hardware. For example, the processes described herein, may be advantageously implemented via processor(s), Digital Signal Processing (DSP) chip, an Application Specific Integrated Circuit (ASIC), Field Programmable Gate Arrays (FPGAs), etc. Such exemplary hardware for performing the described functions is detailed below. 
       FIG. 8  illustrates a computer system  800  upon which an embodiment of the invention may be implemented. Although computer system  800  is depicted with respect to a particular device or equipment, it is contemplated that other devices or equipment (e.g., network elements, servers, etc.) within  FIG. 8  can deploy the illustrated hardware and components of system  8 . Computer system  800  is programmed (e.g., via computer program code or instructions) to pairing advertisements to content items using distribution characteristics as described herein and includes a communication mechanism such as a bus  810  for passing information between other internal and external components of the computer system  800 . Information (also called data) is represented as a physical expression of a measurable phenomenon, typically electric voltages, but including, in other embodiments, such phenomena as magnetic, electromagnetic, pressure, chemical, biological, molecular, atomic, sub-atomic and quantum interactions. For example, north and south magnetic fields, or a zero and non-zero electric voltage, represent two states (0, 1) of a binary digit (bit). Other phenomena can represent digits of a higher base. A superposition of multiple simultaneous quantum states before measurement represents a quantum bit (qubit). A sequence of one or more digits constitutes digital data that is used to represent a number or code for a character. In some embodiments, information called analog data is represented by a near continuum of measurable values within a particular range. Computer system  800 , or a portion thereof, constitutes a means for performing one or more steps of pairing advertisements to content items using distribution characteristics. 
     A bus  810  includes one or more parallel conductors of information so that information is transferred quickly among devices coupled to the bus  810 . One or more processors  802  for processing information are coupled with the bus  810 . 
     A processor (or multiple processors)  802  performs a set of operations on information as specified by computer program code related to pairing advertisements to content items using distribution characteristics. The computer program code is a set of instructions or statements providing instructions for the operation of the processor and/or the computer system to perform specified functions. The code, for example, may be written in a computer programming language that is compiled into a native instruction set of the processor. The code may also be written directly using the native instruction set (e.g., machine language). The set of operations include bringing information in from the bus  810  and placing information on the bus  810 . The set of operations also typically include comparing two or more units of information, shifting positions of units of information, and combining two or more units of information, such as by addition or multiplication or logical operations like OR, exclusive OR (XOR), and AND. Each operation of the set of operations that can be performed by the processor is represented to the processor by information called instructions, such as an operation code of one or more digits. A sequence of operations to be executed by the processor  802 , such as a sequence of operation codes, constitute processor instructions, also called computer system instructions or, simply, computer instructions. Processors may be implemented as mechanical, electrical, magnetic, optical, chemical or quantum components, among others, alone or in combination. 
     Computer system  800  also includes a memory  804  coupled to bus  810 . The memory  804 , such as a random access memory (RAM) or any other dynamic storage device, stores information including processor instructions for pairing advertisements to content items using distribution characteristics. Dynamic memory allows information stored therein to be changed by the computer system  800 . RAM allows a unit of information stored at a location called a memory address to be stored and retrieved independently of information at neighboring addresses. The memory  804  is also used by the processor  802  to store temporary values during execution of processor instructions. The computer system  800  also includes a read only memory (ROM)  806  or any other static storage device coupled to the bus  810  for storing static information, including instructions, that is not changed by the computer system  800 . Some memory is composed of volatile storage that loses the information stored thereon when power is lost. Also coupled to bus  810  is a non-volatile (persistent) storage device  808 , such as a magnetic disk, optical disk or flash card, for storing information, including instructions, that persists even when the computer system  800  is turned off or otherwise loses power. 
     Information, including instructions for pairing advertisements to content items using distribution characteristics, is provided to the bus  810  for use by the processor from an external input device  812 , such as a keyboard containing alphanumeric keys operated by a human user, a microphone, an Infrared (IR) remote control, a joystick, a game pad, a stylus pen, a touch screen, or a sensor. A sensor detects conditions in its vicinity and transforms those detections into physical expression compatible with the measurable phenomenon used to represent information in computer system  800 . Other external devices coupled to bus  810 , used primarily for interacting with humans, include a display device  814 , such as a cathode ray tube (CRT), a liquid crystal display (LCD), a light emitting diode (LED) display, an organic LED (OLED) display, a plasma screen, or a printer for presenting text or images, and a pointing device  816 , such as a mouse, a trackball, cursor direction keys, or a motion sensor, for controlling a position of a small cursor image presented on the display  814  and issuing commands associated with graphical elements presented on the display  814 . In some embodiments, for example, in embodiments in which the computer system  800  performs all functions automatically without human input, one or more of external input device  812 , display device  814  and pointing device  816  is omitted. 
     In the illustrated embodiment, special purpose hardware, such as an application specific integrated circuit (ASIC)  820 , is coupled to bus  810 . The special purpose hardware is configured to perform operations not performed by processor  802  quickly enough for special purposes. Examples of ASICs include graphics accelerator cards for generating images for display  814 , cryptographic boards for encrypting and decrypting messages sent over a network, speech recognition, and interfaces to special external devices, such as robotic arms and medical scanning equipment that repeatedly perform some complex sequence of operations that are more efficiently implemented in hardware. 
     Computer system  800  also includes one or more instances of a communications interface  870  coupled to bus  810 . Communication interface  870  provides a one-way or two-way communication coupling to a variety of external devices that operate with their own processors, such as printers, scanners and external disks. In general the coupling is with a network link  878  that is connected to a local network  880  to which a variety of external devices with their own processors are connected. For example, communication interface  870  may be a parallel port or a serial port or a universal serial bus (USB) port on a personal computer. In some embodiments, communications interface  870  is an integrated services digital network (ISDN) card or a digital subscriber line (DSL) card or a telephone modem that provides an information communication connection to a corresponding type of telephone line. In some embodiments, a communication interface  870  is a cable modem that converts signals on bus  810  into signals for a communication connection over a coaxial cable or into optical signals for a communication connection over a fiber optic cable. As another example, communications interface  870  may be a local area network (LAN) card to provide a data communication connection to a compatible LAN, such as Ethernet. Wireless links may also be implemented. For wireless links, the communications interface  870  sends or receives or both sends and receives electrical, acoustic or electromagnetic signals, including infrared and optical signals, that carry information streams, such as digital data. For example, in wireless handheld devices, such as mobile telephones like cell phones, the communications interface  870  includes a radio band electromagnetic transmitter and receiver called a radio transceiver. In certain embodiments, the communications interface  870  enables connection to the communication network  111  for pairing advertisements to content items using distribution characteristics to the UE  101 . 
     The term “computer-readable medium” as used herein refers to any medium that participates in providing information to processor  802 , including instructions for execution. Such a medium may take many forms, including, but not limited to computer-readable storage medium (e.g., non-volatile media, volatile media), and transmission media. Non-transitory media, such as non-volatile media, include, for example, optical or magnetic disks, such as storage device  808 . Volatile media include, for example, dynamic memory  804 . Transmission media include, for example, twisted pair cables, coaxial cables, copper wire, fiber optic cables, and carrier waves that travel through space without wires or cables, such as acoustic waves and electromagnetic waves, including radio, optical and infrared waves. Signals include man-made transient variations in amplitude, frequency, phase, polarization or other physical properties transmitted through the transmission media. Common forms of computer-readable media include, for example, a floppy disk, a flexible disk, hard disk, magnetic tape, any other magnetic medium, a CD-ROM, CDRW, DVD, any other optical medium, punch cards, paper tape, optical mark sheets, any other physical medium with patterns of holes or other optically recognizable indicia, a RAM, a PROM, an EPROM, a FLASH-EPROM, an EEPROM, a flash memory, any other memory chip or cartridge, a carrier wave, or any other medium from which a computer can read. The term computer-readable storage medium is used herein to refer to any computer-readable medium except transmission media. 
     Logic encoded in one or more tangible media includes one or both of processor instructions on a computer-readable storage media and special purpose hardware, such as ASIC  820 . 
     Network link  878  typically provides information communication using transmission media through one or more networks to other devices that use or process the information. For example, network link  878  may provide a connection through local network  880  to a host computer  882  or to equipment  884  operated by an Internet Service Provider (ISP). ISP equipment  884  in turn provides data communication services through the public, world-wide packet-switching communication network of networks now commonly referred to as the Internet  890 . 
     A computer called a server host  892  connected to the Internet hosts a process that provides a service in response to information received over the Internet. For example, server host  892  hosts a process that provides information representing video data for presentation at display  814 . It is contemplated that the components of system  800  can be deployed in various configurations within other computer systems, e.g., host  882  and server  892 . 
     At least some embodiments of the invention are related to the use of computer system  800  for implementing some or all of the techniques described herein. According to one embodiment of the invention, those techniques are performed by computer system  800  in response to processor  802  executing one or more sequences of one or more processor instructions contained in memory  804 . Such instructions, also called computer instructions, software and program code, may be read into memory  804  from another computer-readable medium such as storage device  808  or network link  878 . Execution of the sequences of instructions contained in memory  804  causes processor  802  to perform one or more of the method steps described herein. In alternative embodiments, hardware, such as ASIC  820 , may be used in place of or in combination with software to implement the invention. Thus, embodiments of the invention are not limited to any specific combination of hardware and software, unless otherwise explicitly stated herein. 
     The signals transmitted over network link  878  and other networks through communications interface  870 , carry information to and from computer system  800 . Computer system  800  can send and receive information, including program code, through the networks  880 ,  890  among others, through network link  878  and communications interface  870 . In an example using the Internet  890 , a server host  892  transmits program code for a particular application, requested by a message sent from computer  800 , through Internet  890 , ISP equipment  884 , local network  880  and communications interface  870 . The received code may be executed by processor  802  as it is received, or may be stored in memory  804  or in storage device  808  or any other non-volatile storage for later execution, or both. In this manner, computer system  800  may obtain application program code in the form of signals on a carrier wave. 
     Various forms of computer readable media may be involved in carrying one or more sequence of instructions or data or both to processor  802  for execution. For example, instructions and data may initially be carried on a magnetic disk of a remote computer such as host  882 . The remote computer loads the instructions and data into its dynamic memory and sends the instructions and data over a telephone line using a modem. A modem local to the computer system  800  receives the instructions and data on a telephone line and uses an infra-red transmitter to convert the instructions and data to a signal on an infra-red carrier wave serving as the network link  878 . An infrared detector serving as communications interface  870  receives the instructions and data carried in the infrared signal and places information representing the instructions and data onto bus  810 . Bus  810  carries the information to memory  804  from which processor  802  retrieves and executes the instructions using some of the data sent with the instructions. The instructions and data received in memory  804  may optionally be stored on storage device  808 , either before or after execution by the processor  802 . 
       FIG. 9  illustrates a chip set or chip  900  upon which an embodiment of the invention may be implemented. Chip set  900  is programmed to pairing advertisements to content items using distribution characteristics as described herein and includes, for instance, the processor and memory components described with respect to  FIG. 9  incorporated in one or more physical packages (e.g., chips). By way of example, a physical package includes an arrangement of one or more materials, components, and/or wires on a structural assembly (e.g., a baseboard) to provide one or more characteristics such as physical strength, conservation of size, and/or limitation of electrical interaction. It is contemplated that in certain embodiments the chip set  900  can be implemented in a single chip. It is further contemplated that in certain embodiments the chip set or chip  900  can be implemented as a single “system on a chip.” It is further contemplated that in certain embodiments a separate ASIC would not be used, for example, and that all relevant functions as disclosed herein would be performed by a processor or processors. Chip set or chip  900 , or a portion thereof, constitutes a means for performing one or more steps of providing user interface navigation information associated with the availability of functions. Chip set or chip  900 , or a portion thereof, constitutes a means for performing one or more steps of pairing advertisements to content items using distribution characteristics. 
     In one embodiment, the chip set or chip  900  includes a communication mechanism such as a bus  901  for passing information among the components of the chip set  900 . A processor  903  has connectivity to the bus  901  to execute instructions and process information stored in, for example, a memory  905 . The processor  903  may include one or more processing cores with each core configured to perform independently. A multi-core processor enables multiprocessing within a single physical package. Examples of a multi-core processor include two, four, eight, or greater numbers of processing cores. Alternatively or in addition, the processor  903  may include one or more microprocessors configured in tandem via the bus  901  to enable independent execution of instructions, pipelining, and multithreading. The processor  903  may also be accompanied with one or more specialized components to perform certain processing functions and tasks such as one or more digital signal processors (DSP)  907 , or one or more application-specific integrated circuits (ASIC)  909 . A DSP  907  typically is configured to process real-world signals (e.g., sound) in real time independently of the processor  903 . Similarly, an ASIC  909  can be configured to performed specialized functions not easily performed by a more general purpose processor. Other specialized components to aid in performing the inventive functions described herein may include one or more field programmable gate arrays (FPGA), one or more controllers, or one or more other special-purpose computer chips. 
     In one embodiment, the chip set or chip  900  includes merely one or more processors and some software and/or firmware supporting and/or relating to and/or for the one or more processors. 
     The processor  903  and accompanying components have connectivity to the memory  905  via the bus  901 . The memory  905  includes both dynamic memory (e.g., RAM, magnetic disk, writable optical disk, etc.) and static memory (e.g., ROM, CD-ROM, etc.) for storing executable instructions that when executed perform the inventive steps described herein to pairing advertisements to content items using distribution characteristics. The memory  905  also stores the data associated with or generated by the execution of the inventive steps. 
       FIG. 10  is a diagram of exemplary components of a mobile terminal (e.g., handset) for communications, which is capable of operating in the system of  FIG. 1 , according to one embodiment. In some embodiments, mobile terminal  1001 , or a portion thereof, constitutes a means for performing one or more steps of pairing advertisements to content items using distribution characteristics. Generally, a radio receiver is often defined in terms of front-end and back-end characteristics. The front-end of the receiver encompasses all of the Radio Frequency (RF) circuitry whereas the back-end encompasses all of the base-band processing circuitry. As used in this application, the term “circuitry” refers to both: (1) hardware-only implementations (such as implementations in only analog and/or digital circuitry), and (2) to combinations of circuitry and software (and/or firmware) (such as, if applicable to the particular context, to a combination of processor(s), including digital signal processor(s), software, and memory(ies) that work together to cause an apparatus, such as a mobile phone or server, to perform various functions). This definition of “circuitry” applies to all uses of this term in this application, including in any claims. As a further example, as used in this application and if applicable to the particular context, the term “circuitry” would also cover an implementation of merely a processor (or multiple processors) and its (or their) accompanying software/or firmware. The term “circuitry” would also cover if applicable to the particular context, for example, a baseband integrated circuit or applications processor integrated circuit in a mobile phone or a similar integrated circuit in a cellular network device or other network devices. 
     Pertinent internal components of the telephone include a Main Control Unit (MCU)  1003 , a Digital Signal Processor (DSP)  1005 , and a receiver/transmitter unit including a microphone gain control unit and a speaker gain control unit. A main display unit  1007  provides a display to the user in support of various applications and mobile terminal functions that perform or support the steps of pairing advertisements to content items using distribution characteristics. The display  1007  includes display circuitry configured to display at least a portion of a user interface of the mobile terminal (e.g., mobile telephone). Additionally, the display  1007  and display circuitry are configured to facilitate user control of at least some functions of the mobile terminal. An audio function circuitry  1009  includes a microphone  1011  and microphone amplifier that amplifies the speech signal output from the microphone  1011 . The amplified speech signal output from the microphone  1011  is fed to a coder/decoder (CODEC)  1013 . 
     A radio section  1015  amplifies power and converts frequency in order to communicate with a base station, which is included in a mobile communication system, via antenna  1017 . The power amplifier (PA)  1019  and the transmitter/modulation circuitry are operationally responsive to the MCU  1003 , with an output from the PA  1019  coupled to the duplexer  1021  or circulator or antenna switch, as known in the art. The PA  1019  also couples to a battery interface and power control unit  1020 . 
     In use, a user of mobile terminal  1001  speaks into the microphone *&#39;11 and his or her voice along with any detected background noise is converted into an analog voltage. The analog voltage is then converted into a digital signal through the Analog to Digital Converter (ADC)  1023 . The control unit  1003  routes the digital signal into the DSP  1005  for processing therein, such as speech encoding, channel encoding, encrypting, and interleaving. In one embodiment, the processed voice signals are encoded, by units not separately shown, using a cellular transmission protocol such as enhanced data rates for global evolution (EDGE), general packet radio service (GPRS), global system for mobile communications (GSM), Internet protocol multimedia subsystem (IMS), universal mobile telecommunications system (UMTS), etc., as well as any other suitable wireless medium, e.g., microwave access (WiMAX), Long Term Evolution (LTE) networks, code division multiple access (CDMA), wideband code division multiple access (WCDMA), wireless fidelity (WiFi), satellite, and the like, or any combination thereof. 
     The encoded signals are then routed to an equalizer  1025  for compensation of any frequency-dependent impairments that occur during transmission though the air such as phase and amplitude distortion. After equalizing the bit stream, the modulator  1027  combines the signal with a RF signal generated in the RF interface  1029 . The modulator  1027  generates a sine wave by way of frequency or phase modulation. In order to prepare the signal for transmission, an up-converter  1031  combines the sine wave output from the modulator  1027  with another sine wave generated by a synthesizer  1033  to achieve the desired frequency of transmission. The signal is then sent through a PA  1019  to increase the signal to an appropriate power level. In practical systems, the PA  1019  acts as a variable gain amplifier whose gain is controlled by the DSP  1005  from information received from a network base station. The signal is then filtered within the duplexer  1021  and optionally sent to an antenna coupler  1035  to match impedances to provide maximum power transfer. Finally, the signal is transmitted via antenna  1017  to a local base station. An automatic gain control (AGC) can be supplied to control the gain of the final stages of the receiver. The signals may be forwarded from there to a remote telephone which may be another cellular telephone, any other mobile phone or a land-line connected to a Public Switched Telephone Network (PSTN), or other telephony networks. 
     Voice signals transmitted to the mobile terminal  1001  are received via antenna  1017  and immediately amplified by a low noise amplifier (LNA)  1037 . A down-converter  1039  lowers the carrier frequency while the demodulator  1041  strips away the RF leaving only a digital bit stream. The signal then goes through the equalizer  1025  and is processed by the DSP  1005 . A Digital to Analog Converter (DAC)  1043  converts the signal and the resulting output is transmitted to the user through the speaker  1045 , all under control of a Main Control Unit (MCU)  1003  which can be implemented as a Central Processing Unit (CPU). 
     The MCU  1003  receives various signals including input signals from the keyboard  1047 . The keyboard  1047  and/or the MCU  1003  in combination with other user input components (e.g., the microphone  1011 ) comprise a user interface circuitry for managing user input. The MCU  1003  runs a user interface software to facilitate user control of at least some functions of the mobile terminal  1001  to pairing advertisements to content items using distribution characteristics. The MCU  1003  also delivers a display command and a switch command to the display  1007  and to the speech output switching controller, respectively. Further, the MCU  1003  exchanges information with the DSP  1005  and can access an optionally incorporated SIM card  1049  and a memory  1051 . In addition, the MCU  1003  executes various control functions required of the terminal. The DSP  1005  may, depending upon the implementation, perform any of a variety of conventional digital processing functions on the voice signals. Additionally, DSP  1005  determines the background noise level of the local environment from the signals detected by microphone  1011  and sets the gain of microphone  1011  to a level selected to compensate for the natural tendency of the user of the mobile terminal  1001 . 
     The CODEC  1013  includes the ADC  1023  and DAC  1043 . The memory  1051  stores various data including call incoming tone data and is capable of storing other data including music data received via, e.g., the global Internet. The software module could reside in RAM memory, flash memory, registers, or any other form of writable storage medium known in the art. The memory device  1051  may be, but not limited to, a single memory, CD, DVD, ROM, RAM, EEPROM, optical storage, magnetic disk storage, flash memory storage, or any other non-volatile storage medium capable of storing digital data. 
     An optionally incorporated SIM card  1049  carries, for instance, important information, such as the cellular phone number, the carrier supplying service, subscription details, and security information. The SIM card  1049  serves primarily to identify the mobile terminal  1001  on a radio network. The card  1049  also contains a memory for storing a personal telephone number registry, text messages, and user specific mobile terminal settings. 
     While the invention has been described in connection with a number of embodiments and implementations, the invention is not so limited but covers various obvious modifications and equivalent arrangements, which fall within the purview of the appended claims. Although features of the invention are expressed in certain combinations among the claims, it is contemplated that these features can be arranged in any combination and order.