Patent Publication Number: US-9886510-B2

Title: Augmenting search results with interactive search matrix

Description:
FIELD OF THE INVENTION 
     The present invention relates generally to internet search engines, and more particularly to search engine indexing utilizing term and keyword detection, subject matter ontologies, and association rule determination. 
     BACKGROUND 
     The use of the Internet has become pervasive, and business entities and individuals use the Internet as a tool for obtaining information regularly. For example, such Internet users use search engines to search numerous World Wide Web sites and/or databases for information relevant to search terms. In recent years, the sophistication of search engines has improved, increasing the ability of search engines to produce search results that accurately reflect the search terms provided by the users. However, in circumstances where users are interested in understanding a broad field, such accuracy can actually be counterproductive. Further, search engines typically present users with a large volume of relevant information, and the users must consider a large portion of the relevant information to comprehensively understand the context of the search results. 
     SUMMARY 
     Embodiments of the present invention provide for a program product, system, and method in which a computer performs a search. The computer receives a search request including a search term, and determines a plurality of association rules that are each a logical implication that the appearance of the search term follows from the appearance, in a corpus of data, of at least one keyword. The computer generates a search matrix having a plurality of cells, and having axes labeled with a plurality of keywords, wherein at least one cell of the search matrix is associated with an association rule of the plurality of association rules. Based on a cell selection of the search matrix, the computer generates an augmented search string including the search term and at least one keyword of the plurality of association rules. 
    
    
     
       BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS 
         FIG. 1  is a block diagram of a search environment in accordance with an embodiment of the present invention. 
         FIGS. 2A and 2B  are illustrations of a user interface depicting a search matrix in accordance with an embodiment of the present invention. 
         FIG. 3  is a flowchart depicting steps followed by a search engine in accordance with an embodiment of the present invention. 
         FIG. 4  is a block diagram of a computer system in accordance with an embodiment of the present invention. 
     
    
    
     DETAILED DESCRIPTION 
     As will be appreciated by one skilled in the art, aspects of the present invention may be embodied as a system, method or computer program product. Accordingly, aspects of the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment (including firmware, resident software, micro-code, etc.) or an embodiment combining software and hardware aspects that may all generally be referred to herein as a “circuit,” “module” or “system.” Furthermore, aspects of the present invention may take the form of a computer program product embodied in one or more computer-readable medium(s) having computer-readable program code embodied thereon. 
     Any combination of one or more computer-readable medium(s) may be utilized. The computer-readable medium may be a computer-readable signal medium or a computer-readable storage medium. A computer-readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of the computer-readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer-readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. 
     A computer-readable signal medium may include a propagated data signal with computer-readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer-readable signal medium may be any computer-readable medium that is not a computer-readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. 
     Program code embodied on a computer-readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing. 
     Computer program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java (note: the term(s) Java may be subject to trademark and/or service mark rights in various jurisdictions throughout the world, and, to that extent, references to this term(s) herein are to be taken to exclusively apply only to legitimate products of the trademark/service mark owner(s)), Smalltalk, C++ or the like and conventional procedural programming languages, such as the “C” programming language or similar programming languages. The program code may execute entirely on the user&#39;s computer, partly on the user&#39;s computer, as a stand-alone software package, partly on the user&#39;s computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user&#39;s computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet Service Provider). 
     Aspects of the present invention are described below with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor (i.e., a computing processor) of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. 
     These computer program instructions may also be stored in a computer-readable medium that can direct a computer, other programmable data processing apparatus, or other devices to function in a particular manner, such that the instructions stored in the computer-readable medium produce an article of manufacture including instructions which implement the function/act specified in the flowchart and/or block diagram block or blocks. 
     The computer program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other devices to cause a series of operational steps to be performed on the computer, other programmable apparatus or other devices to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide processes for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. 
     Referring now to  FIG. 1 , a block diagram of search environment  100  in accordance with an embodiment of the present invention is shown. Search environment  100  includes network  110 , user computer  120 , servers  130 , and search engine  140 . Network  110  can be, for example, a local area network (LAN), a wide area network (WAN) such as the Internet, or a combination of the two, and can include wired or wireless connections. In general, network  110  can be any combination of connections and protocols that will support communications between user computer  120 , servers  130 , and search engine  140  in accordance with an embodiment of the invention. As will be discussed in detail below, person  102 , a user of search environment  100 , can utilize user computer  120  to search for a search term using search engine  140 , and to interact with a resulting search matrix, generated by search engine  140 , on user interface  104  of user computer  120 . 
     In various embodiments, user computer  120 , each one of servers  130 , as well as search engine  140 , can include a laptop, tablet, or netbook personal computer, a desktop computer, a personal digital assistant, a smart phone, a mainframe computer, or a networked server computer. Further, user computer  120 , each one of servers  130 , as well as search engine  140 , can include computing systems utilizing clustered computers and components to act as single pools of seamless resources when accessed through network  110 , or can represent one or more cloud computing datacenters. In general, user computer  120 , each one of servers  130 , as well as search engine  140 , can be any programmable electronic device as described in further detail below with respect to  FIG. 4 . 
     User computer  120  includes software, such as a web browser program, for interacting with search engine  140 , and optionally with one or more of servers  130 , via network  110 . For example, one or more of servers  130  can host web pages viewable on the web browser program of user computer  120 . For another example, the web browser program of user computer  120  can load a search interface web page from search program  148  of search engine  140 , in order to make a search request. In particular, person  102  can enter a search term into the loaded search interface web page displayed by the web browser program, and the web browser program can make a search request by transmitting the search term back to search program  148 . Subsequently, search program  148  can generate a search matrix (e.g., search matrix  260  depicted in  FIG. 2A , etc.) and transmit the search matrix to user computer  120  as discussed in detail below. Additionally, person  102  can interact with the search matrix to select one or more cells for augmented searching, as further discussed in detail below. 
     Search engine  140  includes crawler program  142 , parser program  144 , indexer program  146 , search program  148 , and search data  150 . Search program  148  provides an interface between search engine  140  and clients of search engine  140  (e.g., one or both of person  102  and user computer  120  can be regarded as clients of search engine  140 , etc.). For example, search program  148  can provide an interface by transmitting a search interface web page to a web browser program of user computer  120 , and then by interacting with person  102  via the search interface web page. Search program  148  also generates a search matrix, and assists person  102  in interacting with the search matrix to select one or more cells for augmented searching, by utilizing a subject-matter ontology stored in search data  150 , as well as by utilizing data that has been stored in search data  150  by crawler program  142 , parser program  144 , and indexer program  146 . 
     Crawler program  142 , parser program  144 , and indexer program  146  operate together to crawl, parse, and index web pages hosted on servers  130 , to facilitate the handling of search requests by search program  148 . The operation of crawler program  142 , parser program  144 , and indexer program  146  can occur continuously, as background processes, such that search requests received by search program  148  are handled using up-to-date information from ongoing crawl, parse, and index operations. Up-to-date information from the operation of crawler program  142 , parser program  144 , and indexer program  146  is stored in search data  150  and accessible by search program  148 . 
     During operation, crawler program  142  locates web pages hosted on servers  130 , fetches the web pages to search engine  140 , and provides the web pages to parser program  144  and indexer program  146  for parsing and indexing, respectively. Crawler program  142  can crawl web pages linked together with URLs by, for example, starting with a list of seed URLs, crawling the seed URLs, and adding any found URLs to the list for further crawling. In various embodiments, crawler program  142  is not limited to crawling web pages hosted on servers  130 , but can also crawl any kind of documents, data stores, or repositories hosted on servers  130  and available for crawling by search engine  140 . 
     As crawler program  142  crawls web pages hosted on servers  130 , crawler program  142  provides the web pages to parser program  144 . Parser program  144  includes the subprograms term program  152 , keyword program  154 , and association rule program  156 . During operation, term program  152  performs search term parsing of each web page, so that indexer program  146  can then construct a term index stored in search data  150 . In particular, term program  152  can tokenize the contents of each web page provided by crawler program  142 , and provide the tokenized contents to indexer program  146  for the construction of a reverse term index. A reverse term index lists each web page that a given term appears in, to facilitate basic handling of search requests, as known in the art. For example, using the term index in search data  150 , search program  148  can handle a search request by looking up the search term of the search request in the term index to find out which web pages the search term appears in, and by returning these web pages to user computer  120  as a basic search result. As will be discussed in detail below, the operation of keyword program  154  and association rule program  156  significantly augment such basic search request handling. 
     During operation, keyword program  154  performs keyword parsing of each web page that parser program  144  receives from crawler program  142 , so that indexer program  146  can then construct a keyword index stored in search data  150 . In particular, keyword program  154  can tokenize the contents of each web page provided by crawler program  142 , identify keywords, and provide the tokenized keywords to indexer program  146  for the construction of a reverse keyword index, listing each web page that a given keyword appears in. In one embodiment, keyword program  154  operates on each web page in isolation, while in another embodiment keyword program  154  operates on a large corpus of multiple web pages during, e.g., a global analysis phase. Keyword program  154  identifies keyword tokens by, for example, utilizing keyword extraction techniques such as those described in or referenced in Kaur et al., “Effective Approaches for Extraction of Keywords,”  IJCSI International Journal of Computer Science Issues , Vol. 7, Issue 6, November 2010; ISSN (online): 1694-0814; pp. 144-148, which is herein incorporated by reference in its entirety. Notably, the contents of the resulting keyword index may be a subset of the contents of the term index described above, because keyword program  154  is more selective in making an identification than term program  152 . Stated another way, a keyword is likely to also be a term, but a term is not as likely to also be a keyword, although exceptions to this rule may be found in certain embodiments. 
     During operation, association rule program  156  extracts association rules from each web page that parser program  144  receives from crawler program  142 , and stores the association rules in a rule index stored in search data  150 . In one embodiment, association rule program  156  also determines and stores the strength of each extracted association rule. Association rule program  156  typically operates on a large corpus of multiple web pages during, e.g., a global analysis phase. Each extracted association rule takes the form of a logical implication that the appearance of a keyword follows from the appearance of at least two other related keywords, i.e., takes the form {keyword  1 , keyword  2 } {keyword  3 }. Association rule program  156  extracts association rules and determines association rule strength by, for example, utilizing association rule extraction techniques such as those described in or referenced in Mahgoub et al., “A Text Mining Technique Using Association Rules Extraction,”  International Journal of Information and Mathematical Sciences,  4:1 2008, pp. 21-28, which is herein incorporated by reference in its entirety. In one embodiment, association rule strength is determined by the support, confidence, or conviction of an association rule. Thus, association rule program  156  extracts association rules amongst the keywords identified by keyword program  154 , and stores the extracted association rules and their strengths in a rule index cross referenced against the keyword index of search data  150 . 
     As discussed above, during operation, crawler program  142  locates web pages hosted on servers  130 , fetches the web pages to search engine  140 , and provides the web pages to parser program  144  and indexer program  146  for parsing and indexing, respectively. During such operation, term program  152 , keyword program  154 , and association rule program  156  populate a term index, keyword index, and rule index stored in search data  150 . As stated above, such operation can occur continuously, as background processes, such that search requests received by search program  148  are handled using up-to-date information from ongoing crawl, parse, and index operations, as well as by using a subject-matter ontology stored in search data  150 . Below, the handling of a search request received by search program  148  will be discussed. 
     During operation, search program  148  receives search requests from, e.g., user computer  120 . For each search request, search program  148  generates a search matrix, and assists with user interaction with the search matrix to select one or more cells for augmented searching, by utilizing the term index, keyword index, rule index, and subject-matter ontology stored in search data  150 . In particular, upon receiving a search request, search program  148  looks up the search term of the search request in the subject matter ontology, to identify ontologically-related terms. A search term can be a word, a phrase, or a string including conjunctively and disjunctively joined words or phrases, for example. 
     For example, if the search term is “mobile phone,” then the subject-matter ontology can identify “location-based services,” “camera,” “touch screen,” and additional ontologically-related terms. Additional ontologically-related terms of this example are discussed in the context of  FIG. 2A , below. Notably, the subject-matter ontology can actually include multiple, potentially-overlapping ontologies for different subject-matter areas. For example, “mobile phone” might share ontologically-related terms with “tablet computing.” In various embodiments, the multiple ontologies can have varying scope. For example, in one embodiment, search data  150  includes a subject-matter ontology limited to a technology scope, such that it includes ontologies for electrical devices and digital computers but not, say, medical conditions. In other embodiments, search data  150  includes subject-matter ontologies dedicated strictly to legal concepts, to automobile data, or to medical data. Still further, in another embodiment search data  150  includes subject-matter ontologies of broad, encyclopedic scope, so that search program  148  can generate a search matrix, and assist with user interaction with the search matrix to select one or more cells for augmented searching, in any conceivable subject-matter area. 
     Having looked up the search term of the search request in the subject matter ontology to identify ontologically-related terms, search program  148  generates a search matrix by utilizing the ontologically-related terms to label axes of the search matrix. An exemplary search matrix, search matrix  260 , is shown in  FIG. 2A  to which discussion now turns. 
     Referring now to  FIG. 2A , an illustration of user interface  104  depicting search matrix  260  in accordance with an embodiment of the present invention is shown. Search matrix  260  is a two-axis matrix, and each axis is labeled with keywords  1  through n, each ontologically-related to a search term of a search request received by search program  148 . Only keywords  1  through  4 , and n, are shown for clarity. In one embodiment, keywords  1  through  3  are “location-based services,” “camera,” and “touch screen” in accordance with an example described above. It should be understood that n, an integer, can be any number of ontologically-related terms found by search program  148  during a look-up of the search term in the subject matter ontology. Within search matrix  260  are a number (e.g., n 2 ) of row-column cells. Search program  148  shades, leaves unshaded, or fills with the text “n/a” each row-column cell, as discussed below.  FIG. 2A  further depicts user selections  262  and  264 , also discussed below. 
     Search program  148  generates search matrix  260  by labeling the axes with keywords  1  through n, by filling in the same-keyword row-column cells on the diagonal of search matrix  260  with “n/a,” and by filling in (e.g., shading, etc.) each dissimilar-keyword row-column cell according to whether or not the keywords intersecting at the cell imply the search term of the search request, according to an association rule stored in the rules index of search data  150 . For example, search program  148  fills in the cell of keyword  1  and keyword  1  with “n/a,” as well as the cell of keyword  2  and keyword  2 , etc., proceeding through the cell of keyword n and keyword n. Further, search program  148  shades the cell of keyword  1  and keyword  2 , shades the cell of keyword  1  and keyword  3 , and leaves unshaded the cell of keyword  1  and keyword  4 . In one embodiment, the intensity of the shading is governed by the strength of the relevant association rule. For example, the cell of keyword  1  and keyword  2  can be shaded lightly if those keywords imply the search term weakly, while the cell of keyword  1  and keyword  3  can be shaded darkly if those keywords imply the search term of the search request strongly. In another embodiment, cells will be shaded at all only if their intersecting keywords imply the search term with a strength exceeding a user threshold. 
     Notably, the shading of cells in search matrix  260  is the same regardless of whether cells are named by row-column intersection or by column-row intersection; i.e., search matrix  260  is reflected identically across the “n/a” diagonal. This is the case because, according to the operation of a given association rule, the statement {keyword  1 , keyword  2 } {search term} is equivalent to the statement {keyword  2 , keyword  1 } {search term}. 
     Having received a search request including a search term, and having then generated search matrix  260  based on the search term, search program  148  transmits search matrix  260  to user computer  120 , where it is displayed to person  102  on user interface  104 . It should be understood that in one embodiment, the visual depiction of search matrix  260  depicted in  FIG. 2A  is generated client-side, at user computer  120 , such that search program  148  does not actually generate a graphical depiction, and instead generates and transmits only a data structure sufficient for user computer  120  to generate the visual depiction of search matrix  260 . Person  102  can then interact with search matrix  260  to select one or more cells for augmented searching. 
     Person  102  can select one or more cells for augmented searching by, for example, selecting one or more cells with a mouse or other pointing device. The selection is transmitted from user computer  102  to search program  148 . Upon receiving a selection of a single cell, for example user selection  262 , search program  148  generates an augmented search string including the search term in the original search request, as well as the keywords intersecting at the selected cell. For example, user selection  262  selects the cell at the intersection of keyword  2  and keyword n, and as such search program  148  generates an augmented search string “search term AND (keyword  2  AND keyword n).” Notably, the augmented search string includes the search term, conjunctively joined with both keywords, themselves also conjunctively joined. 
     Further, upon receiving a selection of multiple cells, for example user selection  264 , search program  148  generates an augmented search string including the search term in the original search request, as well as the keywords intersecting at all of the selected cells. For example, user selection  264  selects the cells at the intersections of keyword  2 , keyword  3 , and keyword  4 . As such, search program  148  generates an augmented search string “search term AND ((keyword  2  AND keyword  3 ) OR (keyword  2  AND keyword  4 )).” Notably, the augmented search string includes the search term conjunctively joined with disjunctively joined sets of conjunctively joined keywords. In particular, in the augmented search string, keyword  2  is conjunctively joined with each of keyword  3  and keyword  4 , in two disjunctive sets. Another selection of multiple cells (not shown) can be made by, for example, selecting an axis label to automatically select all of the cells in the label&#39;s row or column (e.g., selecting the keyword  2  column label will have the effect of selecting both cells of user selection  264 , as well as all of the additional cells in the same column). 
     Having generated an augmented search string including the search term in the original search request, as well as the keywords intersecting at the one or more selected cells, search program  148  performs a search using data in search data  150  to return an augmented search result to user computer  120 . For example, search program  148  can perform a search by locating web pages that include that include the logical combination of search terms and keywords in the augmented search string in the term index of search data  150 . Having located such relevant web pages, search program  148  returns them to user computer  120  as an augmented search result, which person  102  can view. 
     Referring now to  FIG. 2B , an illustration of user interface  104  depicting search matrix  261  in accordance with an embodiment of the present invention is shown. Search matrix  261  is similar in most regards to search matrix  260 , except that search program  148  has not filled in the same-keyword row-column cells on the diagonal of search matrix  260  with “n/a.” Instead, search program  148  has filled in (e.g., with shading, etc.) every row-column cell according to whether or not the keywords intersecting at the cell imply the search term of the search request, according to an association rule stored in the rules index of search data  150 . Notably, in this embodiment each extracted association rule can take the form of a logical implication that the appearance of a keyword follows from the appearance of at least one other related keyword, e.g., can take the form {keyword  2 } {search term}. As such, in the context of  FIG. 2B , search program  148  can generate an augmented search string including the search term in the original search request, as well as the single keyword intersecting at a selected cell on the diagonal of search matrix  261 . 
     Referring now to  FIG. 3 , flowchart  302  depicts steps followed by search engine  140  in accordance with an embodiment of the present invention. In step  310 , crawler program  142  crawls servers  130  to fetch web pages. In step  312 , term program  152  of parser program  144  parses the web pages to extract terms to construct a term index in search data  150 . In step  314 , keyword program  154  of parser program  144  parses the web pages to extract keywords to construct a keyword index in search data  150 . In step  316 , association rule program  156  of parser program  144  extracts association rules and determine their strengths to construct a rule index in search data  150 . 
     In step  318 , search program  148  receives a search request including a search term from user computer  120 . In step  320 , search program  148  looks up the search term in a subject-matter ontology in search data  150  to identify ontologically-related terms of the search term. In step  322 , search program  148  generates a search matrix, such as search matrix  260  or search matrix  261 , and transmits the generated search matrix to user computer  120 . In step  324 , search program  148  receives a cell selection of one or more cells of the generated search matrix from user computer  120 . In step  326 , search program  148  generates an augmented search string based on the cell selection, and performs a search to generate an augmented search result. In step  328 , search program  148  transmits the augmented search result to user computer  120 . 
     Referring now to  FIG. 4 , a block diagram of a computer system in accordance with an embodiment of the present invention is shown. Computer system  400  is only one example of a suitable computer system and is not intended to suggest any limitation as to the scope of use or functionality of embodiments of the invention described herein. Regardless, computer system  400  is capable of being implemented and/or performing any of the functionality set forth hereinabove. 
     In computer system  400  there is computer  412 , which is operational with numerous other general purpose or special purpose computing system environments or configurations. Examples of well-known computing systems, environments, and/or configurations that may be suitable for use with computer  412  include, but are not limited to, personal computer systems, server computer systems, thin clients, thick clients, handheld or laptop devices, multiprocessor systems, microprocessor-based systems, set top boxes, programmable consumer electronics, network PCs, minicomputer systems, mainframe computer systems, and distributed cloud computing environments that include any of the above systems or devices, and the like. User computer  120 , each one of servers  130 , as well as search engine  140 , can include or can be implemented as an instance of computer  412 . 
     Computer  412  may be described in the general context of computer system executable instructions, such as program modules, being executed by a computer system. Generally, program modules may include routines, programs, objects, components, logic, data structures, and so on that perform particular tasks or implement particular abstract data types. Computer  412  may be practiced in distributed cloud computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed cloud computing environment, program modules may be located in both local and remote computer system storage media including memory storage devices. 
     As further shown in  FIG. 4 , computer  412  in computer system  400  is shown in the form of a general-purpose computing device. The components of computer  412  may include, but are not limited to, one or more processors or processing units  416 , memory  428 , and bus  418  that couples various system components including memory  428  to processing unit  416 . 
     Bus  418  represents one or more of any of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, and a processor or local bus using any of a variety of bus architectures. By way of example, and not limitation, such architectures include Industry Standard Architecture (ISA) bus, Micro Channel Architecture (MCA) bus, Enhanced ISA (EISA) bus, Video Electronics Standards Association (VESA) local bus, and Peripheral Component Interconnect (PCI) bus. 
     Computer  412  typically includes a variety of computer system readable media. Such media may be any available media that is accessible by computer  412 , and includes both volatile and non-volatile media, and removable and non-removable media. 
     Memory  428  can include computer system readable media in the form of volatile memory, such as random access memory (RAM)  430  and/or cache  432 . Computer  412  may further include other removable/non-removable, volatile/non-volatile computer system storage media. By way of example only, storage system  434  can be provided for reading from and writing to a non-removable, non-volatile magnetic media (not shown and typically called a “hard drive”). Although not shown, a magnetic disk drive for reading from and writing to a removable, non-volatile magnetic disk (e.g., a “floppy disk”), and an optical disk drive for reading from or writing to a removable, non-volatile optical disk such as a CD-ROM, DVD-ROM or other optical media can be provided. In such instances, each can be connected to bus  418  by one or more data media interfaces. As will be further depicted and described below, memory  428  may include at least one program product having a set (e.g., at least one) of program modules that are configured to carry out the functions of embodiments of the invention. 
     Program  440 , having one or more program modules  442 , may be stored in memory  428  by way of example, and not limitation, as well as an operating system, one or more application programs, other program modules, and program data. Each of the operating system, one or more application programs, other program modules, and program data or some combination thereof, may include an implementation of a networking environment. Program modules  442  generally carry out the functions and/or methodologies of embodiments of the invention as described herein. Crawler program  142 , parser program  144 , indexer program  146 , search program  148 , term program  152 , keyword program  154 , and association rule program  156  can be implemented as or can be an instance of program  440 . 
     Computer  412  may also communicate with one or more external devices  414  such as a keyboard, a pointing device, or one or more devices that enable a user to interact with computer  412 , such as via user interface  104  on display  424 ; and/or any devices (e.g., network card, modem, etc.) that enable computer  412  to communicate with one or more other computing devices. Such communication can occur via Input/Output (I/O) interfaces  422 . Still yet, computer  412  can communicate with one or more networks such as a local area network (LAN), a general wide area network (WAN), and/or a public network (e.g., the Internet) via network adapter  420 . As depicted, network adapter  420  communicates with the other components of computer  412  via bus  418 . It should be understood that although not shown, other hardware and/or software components could be used in conjunction with computer  412 . Examples, include, but are not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data archival storage systems, etc. 
     The flowchart and block diagrams in the Figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the Figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems that perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.