Patent Document

CROSS-REFERENCE TO RELATED APPLICATIONS 
     This application claims priority to U.S. Provisional Application 60/935,650, filed Aug. 23, 2007 and entitled DECISION MAKING AND ADVERTISING ENGINE, the entire contents of which are hereby incorporated by reference. 
    
    
     BACKGROUND OF THE INVENTION 
     Existing online search tools, such as Google, Yahoo and Microsoft, provide searching parties with near-instantaneous access to extremely broad amounts of products and data. Generally, the data sought by the searching parties is used to assist resolving a problem or providing assistance in a decision making process. In some known searches, the searching party is interested in purchasing a particular product from a group of similar products. The data returned from these searches is generally not returned or displayed in a manner that is helpful to the searching party. Moreover, known search engines do not return decision making search results that encompass the factors used in a decision or the importance of the factors in the decision. 
     Some known search engines and search tools return the search results in a list form, which provide little guidance to the searching party as to what search result or results may be most relevant. As a result, the searching party is required to spend additional time attempting to tabulate and compare the returned data. As such, the searching party is required to use an additional application to acquire the search results. 
     Also, advertisers desire to present advertisements to searching parties. Generally advertisers are required to purchase keywords that, when searched, will display an advertisement from the advertiser. However, because many keywords are extremely broad, the bidding for keywords is often very expensive and results in the display of advertisements that are not relevant to the searching party&#39;s desired search results. 
     BRIEF DESCRIPTION OF THE INVENTION 
     In one exemplary embodiment, a method of comparing a plurality of decision options is provided. The method can include entering a plurality of factors; determining a plurality of decision options based on the plurality of factors; calculating a score for the plurality of factors; ranking each decision option based on the total score of each factor; outputting the rankings for each decision option. 
     In another exemplary embodiment, a computer program embodied on a computer-readable medium is provided. The computer program may include at least one code segment configured to instruct a computer to receive a plurality of factors; determine a plurality of decision options based on the plurality of factors; calculate a score for the plurality of factors; rank the plurality of decision options based on the total score of each factor; output the rank of the plurality of decision options. 
     In yet another exemplary embodiment, a decision making system is provided. The system may include at least one server coupled in communication with at least one first party and at least one second party, the at least one server configured to receive a plurality of factors; determine a plurality of decision options based on the plurality of factors; calculate a score for the plurality of factors; rank the plurality of decision options based on the total score of the plurality of factors of each decision option; output the rank of the plurality of decision options. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       Advantages of embodiments of the present invention will be apparent from the following detailed description of the exemplary embodiments. The following detailed description should be considered in conjunction with the accompanying figures in which: 
         FIG. 1  is a schematic illustration of a decision making system; 
         FIG. 2  is an enlarged schematic illustration of the system shown in  FIG. 1 ; 
         FIG. 3  is an illustration of a factors data entry page that may be used with the system shown in  FIG. 1 ; 
         FIG. 4  is an illustration of a graph factors page that may be used with the system shown in  FIG. 1 ; 
         FIG. 5  is an illustration of a decision options page that may be used with the system shown in  FIG. 1 ; 
         FIG. 6  is an illustration of a raw data page that may be used with the system shown in  FIG. 1 ; 
         FIG. 7  is an illustration of a score results page that may be used with the system shown in  FIG. 1 ; 
         FIG. 8  is an illustration of a graph results page that may be used with the system shown in  FIG. 1 ; 
         FIG. 9  is an illustration of a page including a pop-up summary window that may be used with the system shown in  FIG. 1 ; and 
         FIG. 10  is a flowchart of a method of comparing different options using the system shown in  FIG. 1 . 
     
    
    
     DETAILED DESCRIPTION OF THE INVENTION 
     Aspects of the present invention are disclosed in the following description and related figures directed to specific embodiments of the invention. Those skilled in the art will recognize that alternate embodiments may be devised without departing from the spirit or the scope of the claims. Additionally, well-known elements of exemplary embodiments of the invention will not be described in detail or will be omitted so as not to obscure the relevant details of the invention. 
     As used herein, the word “exemplary” means “serving as an example, instance or illustration.” The embodiments described herein are not limiting, but rather are exemplary only. It should be understood that the described embodiments are not necessarily to be construed as preferred or advantageous over other embodiments. Moreover, the terms “embodiments of the invention”, “embodiments” or “invention” do not require that all embodiments of the invention include the discussed feature, advantage or mode of operation. 
     Further, many of the embodiments described herein are described in terms of sequences of actions to be performed by, for example, elements of a computing device. It should be recognized by those skilled in the art that the various sequence of actions described herein can be performed by specific circuits (e.g., application specific integrated circuits (ASICs)) and/or by program instructions executed by at least one processor. Additionally, the sequence of actions described herein can be embodied entirely within any form of computer-readable storage medium such that execution of the sequence of actions enables the processor to perform the functionality described herein. Thus, the various aspects of the present invention may be embodied in a number of different forms, all of which have been contemplated to be within the scope of the claimed subject matter. In addition, for each of the embodiments described herein, the corresponding form of any such embodiments may be described herein as, for example, “a computer configured to” perform the described action. 
       FIG. 1  is a schematic illustration of a decision making system  100 .  FIG. 2  is an enlarged schematic illustration of system  100 . In the exemplary embodiment, system  100  may include a web portal  102 , at least one first user  104  and at least one second user  106 . In the exemplary embodiment, each first user  104  and each second user  106  may be coupled in communication to web portal  102  using a network  110 . In the exemplary embodiment, network  110  may be the Internet. In an alternative embodiment, network  110  may be a local area network (LAN), a wireless LAN, a wide area network (WAN) and/or any other type of connection that enables system  100  to function as described herein. System  100 , in the exemplary embodiment, may also include at least one server  112  and at least one database  114 . In the exemplary embodiment, server  112  may be coupled in communication to database  114  using a network connection  115  that is coupled to a local network  116  such as, but not limited to, a LAN, a wireless LAN, a WAN and/or any other connection that enables system  100  to function as described herein. 
     In the exemplary embodiment, first users  104  may be any entity that desires to make a decision on a plurality of decision options using a plurality of factors. Each factor represents a specific consideration that a user may take into account when selecting the decision option. System  100  may be used with decision analyses including, but not limited to, the purchase of any type of products or services, the purchase of any type of real estate, determining which school to attend, determining which career path to pursue or any other decision. In one embodiment, first users  104  may be the general public. Second users  106  may be any entity that is interested in the decision analysis conducted by first users  104 . In one embodiment, second users  106  may be any entity that desires to advertise decision options to first users  104 . In another embodiment, second users  106  may include, but not limited to, advertising agencies, advertisers and specific product entities. 
     In the exemplary embodiment, server  112  may include at least one engine  118  programmed therein. Alternatively, a plurality of servers  112  may be used, wherein each server  112  may include at least one engine  118  programmed therein. As used herein, the term “engine” may refer to a collection of logic and/or code that may be executed on server  112  or any other type of device or processor that is capable of producing a response. In the exemplary embodiment, first engine  118  may be a decision engine. In one embodiment, server  112  may include a second engine (not shown) that may be a connector engine and a third engine (not shown) that may be a marketing engine. In another embodiment, server  112  may include any type of engines or any number of engines that enable system  100  to function as described herein. 
     In the exemplary embodiment, the term “server” is not limited to just those integrated circuits referred to in the art as a computer, but broadly refers to a processor, a microcontroller, a microcomputer, a programmable logic controller, an application specific integrated circuit and other programmable circuits. These aforementioned terms may be used interchangeably herein. In the exemplary embodiment, server  112  may include a bus  130  or other communication mechanism for communicating information, and a processor  132  coupled with bus  130  for processing the information. In one embodiment, a plurality of processors  132  may be arranged in a multi-processor arrangement to facilitate faster processing as compared to a single processor arrangement. In the exemplary embodiment, system  100  may also include a main memory  134 , such as a random access memory (RAM) or other dynamic storage device (e.g., dynamic RAM (DRAM), static RAM (SRAM) and synchronous DRAM (SDRAM)) coupled to bus  130  for storing information and instructions to be executed by processor  132 . In addition, main memory  134  may be used for storing temporary variables or other intermediate information during the execution of instructions by processor  132 . System  100  may further include a read only memory (ROM)  136  or other static storage device (e.g., programmable ROM (PROM), erasable PROM (EPROM) and electrically erasable PROM (EEPROM)) coupled to bus  130  for storing static information and instructions for processor  132 . 
     System  100  may also include a disk controller  138  coupled to bus  130  to control one or more storage devices for storing information and instructions. In the exemplary embodiment, storage devices may include, but not limited to, a magnetic hard disk  140  and a removable media drive  142  (e.g., floppy disk drive, read-only compact disc drive, read/write compact disc drive, compact disc jukebox, tape drive and removable magneto-optical drive). The storage devices may be coupled to system  100  using any appropriate device interface known to one having ordinary skill in the art (e.g., small computer system interface (SCSI), integrated device electronics (IDE), enhanced-IDE (E-IDE), direct memory access (DMA), or ultra-DMA). System  100  may also include special purpose logic devices (e.g., application specific integrated circuits (ASICs)) or configurable logic devices (e.g., simple programmable logic devices (SPLDs), complex programmable logic devices (CPLDs), and field programmable gate arrays (FPGAs)). 
     In the exemplary embodiment, main memory  134 , hard disk  140  and removable media drive  142  are examples of computer-readable mediums that facilitate holding instructions programmed according to the teachings of the invention, data structures, tables, records and/or other data described herein. The term “computer-readable medium” or “computer-readable media” as used herein refers to any medium that facilitates storing and/or providing instructions to processor  132  for the execution thereof. The computer-readable media may include, but not limited to, non-volatile media, volatile media and transmission media. Non-volatile media may include, but not limited to, hard disks, floppy disks, tape, magneto-optical disks, PROMs (EPROM, EEPROM, flash EPROM), DRAM, SRAM, SDRAM or any other magnetic medium. Moreover, non-volatile media may also include compact discs (e.g., CD-ROM) or any other optical medium. Further, non-volatile media may include punch cards, paper tape or other physical medium with patterns of holes. Volatile media may include dynamic memory, such as main memory  134 . Transmission media may include coaxial cables, copper wire and fiber optics, including the wires that make up bus  130 . Transmission media may also include carrier waves such as acoustic or light waves that may be generated using radio waves and infrared data communications. 
     In the exemplary embodiment, the computer-readable media may include software that facilitates controlling system  100 . Such software may include, but is not limited to, device drivers, operating systems, development tools and applications software. Such computer-readable media further includes the computer program product of the present invention for performing all or a portion (if processing is distributed) of the processing performed in implementing the invention. 
     The computer code devices of the present invention may be any interpretable or executable code mechanism, including but not limited to scripts, interpretable programs, dynamic link libraries (DLLs), Java classes, and complete executable programs. Moreover, parts of the processing of the present invention may be distributed for better performance, reliability, and/or cost. 
     In the exemplary embodiment, system  100  may further include a display controller  144  coupled to bus  130  to control a display  146 , such as a cathode ray tube (CRT), liquid crystal display (LCD) or any other type of display to facilitate displaying information to a computer user. System  100  may include a plurality of input devices, such as a keyboard  148  and a pointing device  150 , to facilitate interacting with the computer user and providing information to processor  132 . Alternatively, a touch screen may be used in conjunction with display  146 . In one embodiment, pointing device  150  may be a mouse, a trackball or a pointing stick for communicating direction information and command selections to processor  132  and for controlling cursor movement on display  146 . In addition, a printer (not shown) may be coupled to system  100  to facilitate printing data stored and/or generated by system  100 . 
     System  100  also includes a communication interface  152  coupled to bus  130 , wherein communication interface  152  may be coupled in communication to LAN  116  or network  110  using network connection  115 . In one embodiment, communication interface  152  may be a network interface card that is coupled in communication to any packet switched LAN. In another embodiment, communication interface  152  may be an asymmetrical digital subscriber line (ADSL) card, an integrated services digital network (ISDN) card or a modem to facilitate providing a data communication connection to network connection  115 . In yet another embodiment, wireless connections may be used to couple communication interface  152  to LAN  116  and/or network  110 . In the exemplary embodiment, communication interface  152  sends and receives electrical, electromagnetic or optical signals that carry digital data to and from system  100 , which are exemplary forms of carrier waves that facilitate transporting information. Network connection  115  facilitates providing data communication between web portal  102  and data devices using networks  116  and  130 . Specifically, network connection  115  may couple first users  104  and/or second users  106  to web portal  102  using at least one of local network  116  and network  110 . System  100  may also transmit and receive data, including program code, through networks  116  and  110  using network connection  115  and communication interface  152 . Moreover, network connection  115  may couple server  112  in communication to a mobile device  132  such as a personal digital assistant (PDA), a laptop computer, a cellular telephone, a smart phone, an ultra-compact mobile device or any other mobile device that enables system  100  to function as described herein. 
     During operation, system  100  may perform a portion or all of the processing steps of the invention in response to processor  132  executing one or more sequences of one or more instructions contained within main memory  134  and/or other forms of computer-readable media. In one embodiment, processor  132  may execute the instructions contained within the computer-readable media. In another embodiment, hard-wired circuitry may be used in place of or in combination with the instructions. Thus, the exemplary embodiments described herein are not limited to any specific combination of hardware circuitry and software. For example, the instructions may initially be carried on a magnetic disk of a remote computer. The remote computer can load the instructions for implementing all or a portion of the present invention remotely into a dynamic memory and send the instructions over a telephone line using a modem. A modem local to system  100  may receive the data on the telephone line and use an infrared transmitter to convert the data to an infrared signal. An infrared detector coupled to bus  130  can receive the data carried in the infrared signal and place the data on bus  130 . Bus  130  carries the data to main memory  134 , from which processor  132  retrieves and executes the instructions. The instructions received by main memory  134  may optionally be stored on hard disk  140  or removable media drive  142  either before or after execution by processor  132 . 
     Other aspects of the invention may include data transmission and Internet-related activities. See Gralla, Preston,  How the Internet Works , Ziff-Davis Press (1996), which is hereby incorporated by reference into this patent application. Still other aspects of the invention may utilize wireless data transmission, such as those described in U.S. Pat. Nos. 6,456,645, 5,818,328 and/or 6,208,445, all of which are hereby incorporated by reference into this patent application. 
       FIG. 3  is an illustration of a factors data entry interface page, or factors page  200  that may be used with decision engine  118 . In the exemplary embodiment, factors page  200  includes a navigation area  202  and a factor data area  204 . Navigation area  202  includes a plurality of radio buttons such as, but not limited to, a factors button  206 , an options button  208 , a data button  210 , a results button  212 , a graph results button  214 , a graph factors button  216 , a clear button  218  and a summary button  220 . Each radio button facilitates directing a user to the respective interface page. In the exemplary embodiment, clear button  218  facilitates hiding a score summary pop-up window  294  (shown in  FIG. 9 ) and summary button  220  facilitates displaying score summary pop-up window  294  on the page. Moreover, navigation area  202  may include a save/load button  222  and a new decisions button  224 . In the exemplary embodiment, save/load button  222  enables the user to either save their decision analysis progress or load a previously saved decision analysis. Additional information may be included when the user saves their results, such as the ability to choose a destination to save a file to, the ability to name the file to be saved and the ability to include a description of the results. Additionally, engine  118  may allow the user to load saved decision analyses as well as delete prior saved results. Moreover, new decisions button  224  enables the user to begin a new decision analysis. 
     Factor data area  204  may include a plurality of data columns  226  and at least one data row  228 . The plurality of data columns  226  may include, but not limited to, a factors column  232 , a first data column  234  and a second data column  236 , wherein each column  232 ,  234  and  236  includes a plurality of data entry fields  238 . Each data row  228  may include an ON/OFF toggle button  244 , an importance indicator  246  and at least one data entry field  238  associated with columns  232 ,  234  and  236 . In the exemplary embodiment, each ON/OFF button  244  facilitates including or excluding the associated data row  228  from the decision analysis performed by engine  118 . Moreover, each importance indicator  246  facilitates indicating the importance of the associated factor that is assigned by the user. In the exemplary embodiment, an aspect of each factor may be indicated in at least one of first and second data columns  234  and  236 . Specifically, in one embodiment, an aspect of each factor may be indicated with a range of values. In another embodiment, an aspect of each factor may be indicated as a subjective assessment. In yet another embodiment, an aspect of each factor may be indicated as at least one of a yes/no answer, a true/false answer, a multiple-choice answer and any other type of entry known by one having ordinary skill in the art. For example, in the event that each factor may be quantified, a most desired value may be entered into first data column  234  and a least desired value may be entered into second data column  236 . In the event that each factor may be represented as a subjective assessment, the user may enter the word “opinion” in at least one of first and second columns  234  and  236 . In the event that each factor may be represented as yes/no or true/false entry, the user may indicate the most desired entry in first data column  234  and the least desired entry in second data column  236 . 
       FIG. 4  is an illustration of a graph factors page  250 . In the exemplary embodiment, the user may navigate to graph factors page  250  by clicking graph factors radio button  216  in navigation area  202  included in graph factors page  250 . Graph factors page  250  may also include a display area  252  that may include a chart  254  that graphically represents the importance of each factor assigned by the user using importance indicator  246 . Specifically, chart  254  includes a y-axis  256  that includes each factor used in the decision process and an x-axis  258  that includes the relative importance of each factor. At least one graph bar  260  is associated with each factor such that graph bar  260  may graphically represent the importance of each factor. Moreover, the relative importance of each factor is displayed by importance percentage basis. In an alternative embodiment, display area  252  may display the factor importance as a pie chart, a list or any other method of displaying information known to one having ordinary skill in the art to enable engine  118  to function as described herein. 
       FIG. 5  is an illustration of a decision options page  252 . In the exemplary embodiment, the user may navigate to decision options page  252  by clicking options radio button  208  in navigation area  202  included in decision options page  252 . Decision options page  252  may also include a decision options area  254  that may include a plurality of data rows  256  that may include a decision option  258  and an ON/OFF toggle button  244  associated therewith. In the exemplary embodiment, and described in more detail below, engine  118  may determine each decision option  258  based on the factors entered by the user in factors page  200 . In one embodiment, the user may indicate a broad category of the desired decision options  258  to which each factor may apply. In another embodiment, engine  118  may automatically determine the decision option  258  category that applies based on the factors entered by the user in factors page  200 . In yet another embodiment, the user may enter a plurality of decision options  258  and a plurality of factors into system  100  to enable engine  118  to decide on an appropriate decision option  258  based on the entered decision options  258  and factors. 
       FIG. 6  is an illustration of a raw data page  260 . In the exemplary embodiment, the user may navigate to data page  260  by clicking data radio button  210  in navigation area  202  included within data page  260 . Data page  260  may also include a data display area  262  that may include at least one data matrix  264 . Specifically, data matrix  264  may include a plurality of data columns  266  associated with each decision option  258  determined by engine  118 . Moreover, data matrix  264  may include a plurality of data rows  268  associated with each factor entered by the user. In the exemplary embodiment, as described in more detail below, engine  118  determines the objective score or rating for each factor for each decision option  258  and displays the values in matrix form. In the exemplary embodiment, each factor score is non-weighted. As a result, data page  260  displays the raw data to the user. For example, as described in more detail below, in the event the factor score may be quantified, a numeric value is displayed. In the event the factor value is an opinion, the value may be displayed as a subjective assessment using a percent scale. For example, a subjective assessment may be displayed as 8 stars out of 10 stars, as described in more detail below. Further, in the event the factor value may be displayed as a yes/no answer or true/false answer, such an answer is displayed. Moreover, in the event the factor score is a multiple choice answer, a single answer choice that applies to the decision option is displayed. For example, if the factor is a color, then the factor score may be indicated as the specific color of the specific decision option. 
       FIG. 7  is an illustration of a score results page  270 . In the exemplary embodiment, the user may navigate to results page  270  by clicking results radio button  212  in navigation area  202  included within results page  270 . Results page  270  may also include a data display area  272  that may include at least one data matrix  274 . Specifically, data matrix  274  may include a plurality of data columns  276  associated with each decision option  258  determined by engine  118 . Moreover, data matrix  264  may also include a plurality of data rows  278  associated with each factor entered by the user. In the exemplary embodiment, as described in more detail below, engine  118  determines the weighted score of each factor using the non-weighted factor score and the importance assigned to the factor by the user. Each weighted factor score for each decision option  258  is displayed in matrix form. In the exemplary embodiment, each weighted factor score is a numeric number that is used to determine a total score for each decision option  258 . 
       FIG. 8  is an illustration of a graph results page  280 . In the exemplary embodiment, the user may navigate to graph results page  280  by clicking graph results radio button  214  in navigation area  202  included in graph results page  280 . Graph results page  280  may also include a display area  282  that may include a chart  284  that graphically represents the score of each decision option  258  determined by engine  118 . Specifically, chart  284  includes a y-axis  286  that includes a plurality of decision options  258  compared by engine  118  and an x-axis  288  that includes the total scores of each decision option  258 . A graph bar  290  is associated with each decision option  258  such that graph bar  290  may graphically represent the total score each decision option  258 . In an alternative embodiment, display area  282  may display the total score as a pie chart, a list or any other method of displaying information known to one having ordinary skill in the art to enable system  100  to function as described herein. 
     In the exemplary embodiment, once the score for each decision option  258  is determined by engine  118 , as shown in  FIG. 9 , the user may click on summary button  220  to display score summary pop-up window  294  on any page. Score summary pop-up window  294  may include a list of the compared decision options  258  and the scores associated with each decision option  258 . 
       FIG. 10  is a flow chart of exemplary method  300  of comparing different options using system  100 . During operation, a user desiring to decide on a decision option may utilize system  100 , and more specifically engine  118 , to facilitate determining which decision option to choose. In one embodiment, system  100  may be utilized or implemented on network  110 , such as, but not limited to, the Internet. Engine  118  may be used with decision analyses including, but not limited to, the purchase of any type of products or services, the purchase of any type of real estate, deciding which school to attend, deciding which career to pursue or any other type of decision analysis. In the exemplary embodiment, the user may begin a new decision analysis by clicking new decisions button  224  in any of the pages shown in  FIGS. 3-9 . In method step  302 , the user may then navigate to factors page  200 , as shown in  FIG. 3 , by clicking factors radio button  206 , wherein the user may enter a plurality of factors, corresponding to various aspects of the desired decision option, into factors column  232 . Moreover, the user may enter specific data for each factor into first data column  234  and/or second data column  236 . The factor data may be quantified by engine  118  according to an importance level assigned to each factor by the user using importance indicator  246 . In method step  304 , once the user has entered the plurality of factors, the factor data and assigned the importance level of each factor, engine  118  may determine a plurality of decision options  258  to be analyzed and compared in the decision analysis, as shown in  FIG. 4 . 
     Although engine  118  may be used with any decision analysis, a non-limiting example pertaining to deciding which automobile the user should purchase is used to describe the operation of engine  118 . In this non-limiting example, engine  118  may analyze and compare various aspects of automobiles to enable the user to make a decision on which automobile to purchase. Specifically, the plurality of factors may represent various aspects of automobiles that the user may use to analyze and compare potential automobiles. For example, factors 1-10 shown in  FIG. 3  may represent, miles per gallon (MPG), cost, miles per tank, interior noise level, appearance, quarter mile time, 0-60 miles per hour (MPH) time, turning radius, anti-lock braking system (ABS) and exterior color, respectively. Once the user enters the plurality of automobile factors into factors column  232  in factors page  200 , the user may enter unique factor data for each factor in at least one of first and second columns  234  and  236 . 
     In the non-limiting vehicle purchasing example, the unique factor data may represent aspects of a potentially acceptable automobile that the user would purchase. In the exemplary embodiment, at least one factor may be represented as a range. For example, the user may be interested in an automobile that can travel between a range of about 10 to about 35 miles per gallon and cost between a range of about $15,000 to about $25,000. Moreover, at least one other factor may be represented as a subjective assessment, a yes/no answer, a true/false answer or a multiple-choice answer. In one embodiment, an automobile factor that may be a subjective assessment may include interior noise level or appearance. In such an embodiment, the user may enter “opinion” in at least one of first and second data columns  234  and  236  for the interior noise level factor. In another embodiment, a factor that may include a yes/no or true/false answer may be whether the automobile has anti-lock brakes installed. In such an embodiment, in the event the user desires an automobile that includes anti-lock brakes, the user may enter “yes” as the best answer in first data column  234  and “no” as the worst answer in second data column  236 . In yet another embodiment, a factor that may include a multiple-choice answer may be the color of the automobile. In such an embodiment, the user may enter “red, green and blue” as the most desired colors in first data column  234  and “white, black and yellow” as the least desired colors in second data column  236 . Lastly, once the user has entered the unique factor data for each factor, the user may assign the importance level to each factor using importance indicator  246 . After the importance level of each factor have been assigned, the user may view a graphical representation of the importance levels of each factor by navigating to graph factors page  250  by clicking the graph factors radio button  216  on any page shown in  FIGS. 3-9 . 
     Once the user has entered the plurality of factors, entered the factor data and assigned the importance level to each factor in factors page  200 , engine  118  may determine a plurality of decision options and output those options in decision options page  252 , for example as shown in  FIG. 5 . In one embodiment, information for a plurality of decision options, such as but not limited to products, may be located on the Internet. In one embodiment, engine  118  may search the Internet or any other network or database for decision option information, which has been tagged and therefore searchable using an Internet search engine or any other tool. In the exemplary embodiment, ten decision options  258  may be returned and displayed in decision options page  252 . Alternatively, any number of decision options  258  may be returned. In the non-limiting vehicle purchasing decision example, decision options A-J may represent different makes and/or models of vehicles that engine  118  determined were relevant to the decision analysis. In the exemplary embodiment, each determined decision option  258  is displayed on a corresponding data row  256  that includes ON/OFF button  244  associated therewith. The user may include the determined decision option  258  in the decision analysis by switching ON/OFF  244  button to “ON” or exclude the determined decision option  258  by switching ON/OFF  244  button to “OFF”. In the exemplary embodiment, all ON/OFF buttons  244  are switched to “ON” which means that all of decision options A-J will be analyzed and compared in the decision analysis. Alternatively, the user may manually provide the plurality of decision options  258  to engine  118 . 
     Once the plurality of decision options  258  have been determined by engine  118 , the factor data for each decision option  258  may be displayed in data page  260 , as shown in  FIG. 6 . In the non-limiting vehicle purchasing decision example, the aspects of each automobile are displayed in data page  260 . For example, decision option A, or automobile A, gets 42 MPG, costs $24,777, gets 600 miles per tank, received 7 out of 8 stars for interior noise level and has an exterior color of red. 
     Referring back to  FIG. 10 , in method step  306 , system  100 , and more specifically engine  118  may calculate a numeric value, or raw value, that represents the overall desirability of each factor. Specifically, engine  118  may calculate a numeric value of the data entered in first data column  234  that represents a best or most desirable value. Further, engine  118  may calculate a numeric value of the factor data entered in second data column  236  that represents a worst or least desirable value. For example, engine  118  may calculate a numeric value of 10, or any other value that represents the best or most desirable value, for factors that include data that is equal to or greater than the data entered in first data column  234 . Similarly, engine  118  may calculate a numeric value of 0, or any other value that represents the worst or least desirable value, for factors that include data that is equal to or less than the data entered in second data column  236 . Moreover, engine  118  may calculate a corresponding numeric value for factors that include data that is between the best and worst values entered in first and second data columns  234  and  236  using an algorithm such as linear computation. In the non-limiting vehicle purchasing decision example, for factor 1, or MPG, the user entered a most desirable MPG of 35 and a least desirable MPG of 10. In such an example, engine  118  may calculate a numeric value of 5 for a decision option having an MPG of 22.5, a numeric value of 2.5 for a decision option having an MPG of 16.25, a numeric value of 7.5 for a decision option having an MPG of 28.75 and so forth and so on. Alternatively, factor data that falls between the best and worst desired values entered in first and second data columns  234  and  236  may have numeric values assigned by engine  118  using polynomial computation, logarithmic computation, power computation, exponential computation, moving average computation or any other computation method that enables engine  118  to function as described herein. 
     In the non-limiting vehicle purchasing decision example, for factor 4, or interior noise level, the user entered “opinion” in at least one of first and second data column  234  and  236 , shown in  FIG. 3 . In the event the decision option  258  includes a subjective assessment or review from a third party that assessment may be used to calculate a numeric value. For example, in one embodiment, the third party automobile review agency may determine that a particular vehicle has a relatively low amount of interior noise and therefore award 7 stars to that vehicle for interior noise. In such an example, engine  118  may calculate the rating percent and convert that percent to the numeric number. For example, 7 out of 10 stars would equal a 70% interior noise rating. Engine  118  may then calculate the interior noise factor as 7. In the event the decision option  258  does not include a subjective assessment for a third party that may be used to calculate a numeric value, engine  118  may inform the user that no numeric value was calculated for that particular factor. 
     In the non-limiting vehicle purchasing decision example, for factor 9, or ABS, the user entered “yes”, or “true”, in first data column  234  and “no”, or “false”, in second data column  236 . In such an example, in the event a vehicle includes ABS, the engine  118  may calculate a numeric value of 10 for factor 9. In the event a vehicle does not include ABS, then engine  118  may calculate a numeric value of 0 for factor 9. 
     In the non-limiting vehicle purchasing decision example, for factor 10, or exterior vehicle color, the user entered “red, green, blue” in first data column  234  and “white, black, yellow” in second data column  236 . In such an example, in the event a vehicle includes an exterior color of red, green or blue, engine  118  may calculate a numeric value of 10 for factor 10. In the event the vehicle includes an exterior color of white, black or yellow, engine  118  may calculate a numeric value of 0 for factor 10. Further, in the event that the vehicle color is neither, red, green, blue, white, black nor yellow, engine  118  may alert the user of the vehicle&#39;s color. 
     In the event the user wishes to exclude a factor from the decision analysis, the user may switch ON/OFF button  240  in the factors page  200  to “OFF” for the factor. As a result, engine  118  will not consider that factor in the decision analysis. 
     In method step  308 , once the numeric value of each factor of each decision option  258  is calculated, system  100 , and more specifically engine  118  may calculate a weighted score for each factor using the importance assigned to each factor by the user. Scores of each factor may be weighted in any manner, for example by applying a higher weight to scores for factors having a greater importance to the user. Further, the weighted scores can be based on any scaling method and should not be limited to the numbers or scales shown herein. In the non-limiting vehicle purchasing decision example, the user ranks factor 1 and 2, or MPG and cost, as the most important factors in the decision analysis and therefore assigns an importance ranking of 100 to factors 1 and 2. Further, in the exemplary embodiment, the user assigned an importance value of 50 to factor 3, or miles per tank. Moreover, the user assigned an importance value of 25 to factors 4-10. As a result, in this example, the user desires an affordable automobile that achieves substantially good gas mileage and may be driven a relatively far distance on a single tank of gas. However, other factors, such as interior noise level, acceleration, turning radius and ABS braking are other factors that, while not as important as cost, MPG and miles per tank, they may influence the decision of the user in one way or another. 
     For example, factor 1, or MPG factor of decision option A, gets 42 MPG. The user indicated that the most desirable MPG for an automobile is 35 MPG. The MPG factor for automobile A is greater than the most desired value and as a result, MPG factor receives a score of 10. Further, the user assigned an importance of 100 for the MPG factor. As a result, the MPG score is multiplied by the importance level. As such, the exemplary weighted score for the MPG factor for automobile A is 10×100=1000, as shown in  FIG. 7 . In the event the MPG was 22.5, as described above, the MPG score would be 5 and the weighted score would be 5×100=500. Moreover, the interior noise level factor received 7 out of 10 stars, therefore, receiving a score of 7. The user assigned an importance level of 25 for this factor. As a result, the weighted score of the interior noise level is 7×25=175. Further, the exterior color of automobile A is red, resulting in a score of 10. The user assigned an importance level of 25 to this factor. As such, the weighted score of the exterior color factor is 10×25=250. Similar calculations are performed for all desired decision options. 
     Once the weighted score for each factor is calculated by engine  118 , the score for each factor and total score for each decision option  258  may be displayed in results page  270 , as shown in  FIG. 7 . In the exemplary embodiment, each automobile, or decision option  258 , is displayed with the weighted score of each factor. Moreover, the total score of each automobile is calculated by engine  118  and displayed for each decision option  258 . In the non-limiting vehicle purchasing decision example, decision option A, or automobile A, received a total score of 2553, automobile B received a total score of 1960, automobile C received a total score of 2359 and automobile D received a total score of 2118. 
     In method step  310 , as shown in  FIG. 10 , engine  118  ranks each decision option based on the total score. In method step  312 , engine  118  displays a graphical representation of the total scores of each decision option, or automobile, may be displayed in graph results page  280 , as shown in  FIG. 8 . In one embodiment, engine  118  may display the ranks of each decision option based on the total score. Once the total scores of each decision option or automobile are calculated by engine  118 , the user may display summary pop-up window  294  on any page by clicking summary button  220 , as shown in  FIG. 9 . Alternatively, summary pop-up window may display any decision analysis information. As such, the user may interpret from  FIG. 8  that automobiles options A and J include a majority of the user&#39;s desired factors. As a result, system  100  enables the user to choose a decision option based on at least one factor. 
     The foregoing description and accompanying figures illustrate the principles, preferred embodiments and modes of operation of the invention. However, the invention should not be construed as being limited to the particular embodiments discussed above. Additional variations of the embodiments discussed above will be appreciated by those skilled in the art. 
     Therefore, the above-described embodiments should be regarded as illustrative rather than restrictive. Accordingly, it should be appreciated that variations to those embodiments can be made by those skilled in the art without departing from the scope of the invention as defined by the following claims.

Technology Category: 3