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Opinion search engine

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1. 0030 At step 230 the opinion search engine 60 may aggregate the opinion data in the opinion metadata database As such the opinion search engine 60 may identify and group all of the opinion data obtained from various web pages on the Internet pertaining to the same subject matter In order to aggregate the opinion data the opinion search engine 60 may determine whether two or more opinion data in the opinion metadata database are duplicative In one implementation duplicative opinion data may include instances when a single user writes the same review for a single product on two different web pages Upon determining that opinion data are duplicative the opinion search engine 60 may remove the duplicative opinion data from the opinion metadata database 0031 In aggregating the opinion data in the opinion meta data database the opinion search engine 60 may determine whether the opinion data pertains to the similar subject matter or objects For instance a first user may add opinion review to a web page about a certain product Here the first user may refer to the certain product according to its specific name which may include the manufacturer s name and the prod uct s version number A second user may also add opinion review about the same product on the same or a different web page The second user however may refer to the certain product according to its generic name without reference to the manufacturer s name or the product s
2. a product with one or more other products having the same or similar values of related properties in order to recommend products Recommending Competitor Products 0047 The opinion search engine 60 may also recommend competitor products to a user Here the opinion search engine 60 may analyze a user s click through log to identify one or more web pages related to a specific product that a user may have accessed by clicking on a search result Upon analyzing the click through log the opinion search engine 60 may iden tify one or more competitor products of the product web pages accessed by theuser The opinion search engine 60 may then recommend these competitor products to the user 0048 In order to determine which products may be com petitors to the specific product the opinion search engine 60 may analyze the click through log and determine which prod uct web pages were accessed by multiple users as indicated in the multiple users click through logs In one implementa tion the opinion search engine 60 may determine that prod ucts may be competitors if multiple users access different product websites after performing a query for a specific prod uct or for a generic product category Identifying Distinguishing Features of a Product 0049 opinion search engine 60 may also identify one or more distinguishing features of a product based on the categorized opinion database The opinion search engine 60 may then display t
3. a percentage of positive reviews about the feature exceeds a percentage of negative reviews about the feature by a second predetermined value determine that the feature of the similar objects is distin guishing when a discrepancy between a first value ofthe feature for a first object and a second value ofthe feature for a second object of the similar objects exceeds a third predetermined value or combinations thereof 16 A computer system comprising at least one processor and a memory comprising program instructions executable by the at least one processor to collect opinion data about one or more objects from the Internet extract metadata about the opinion data from the opinion data remove duplicate metadata from the metadata to gener ate a resulting metadata categorize the resulting metadata for similar objects according to one or more taxonomies from one or more websites on the Internet receive one or more features about the similar objects and a minimum percentage of positive reviews for each feature and display the similar objects having the features and meet ing the minimum percentage of positive reviews 17 The computer system of claim 16 wherein the memory further comprises program instructions executable by the at least one processor to display a trend indicating whether a number of reviews about one ofthe similar objects is rising or falling over a time period 18 The computer system of claim 16 where
4. certain portions of the operations might be executed in a different order In one implementation the method for implementing an opinion search engine may be performed by the opinion search engine 60 0022 At step 210 the opinion search engine 60 may col lect opinion data from the Internet The opinion data may include reviews or ratings pertaining to an object or subject matter of interest that may be displayed on the Internet In one implementation the opinion search engine 60 may first access every website and web page available on the Internet The web pages available on the Internet may include blogs newsgroups forums and other forms of web based informa tion that may be accessible by the opinion search engine 60 via the Internet After accessing each web page the opinion search engine 60 may then determine whether the web page contains opinion data about an object Opinion data about the objects may relate to reviews about consumer products vaca tion locations or any other subject matter that may be of interest to a user Upon determining that the web page includes opinion data the opinion search engine 60 may store the corresponding web page and the information on the web page in an opinion database The web pages and the informa tion on the web pages stored on the opinion database include a subset of the web pages available on the Internet In one implementation the opinion database may be stored on a server such that the serve
5. cn 0 RANK OPINION DATA Mar 31 2011 Sheet 1 of 4 US 2011 0078157 A1 Patent Application Publication gt ALOWSY WALSAS J3Svaviva MYOMLAN 3NION3 HO4V3S NOINIdO 1 SIAVHOOHd ASIA NOILVOl lddV OIL3NOVIN SIG WALSAS SNILVH3dO 86 09 9 96 SC 9c Vc Patent Application Publication Mar 31 2011 Sheet 2 of 4 US 2011 0078157 A1 200 2 0 COLLECT OPINION DATA FROM INTERNET q 220 EXTRACT METADATA FROM OPINION DATA 230 AGGREGATE METADATA X 240 CATEGORIZE METADATA 250 RANK OPINION DATA FIG 2 US 2011 0078157 1 Mar 31 2011 Sheet 3 of 4 Patent Application Publication 310 1 1 262 25 iat 74 ORZ YA YA T FIG 3 US 2011 0078157 A1 Mar 31 2011 Sheet 4 of 4 Patent Application Publication RM POSITIVE NEGATIVE TOTAL TOTAL POSITIVE lt x 2 3 2 1 0 1 FIG 4 US 2011 0078157 A1 OPINION SEARCH ENGINE BACKGROUND 0001 Internet users reviewers use various web based forums such as blogs and review websites to expre
6. data to its users The opinion search engine 60 may also provide opinion data search results based on the similarities between demo graphic details of the opinion data and the demographic details of the user Mar 31 2011 0059 Although the subject matter has been described in language specific to structural features and or methodologi cal acts it is to be understood that the subject matter defined in the appended claims is not necessarily limited to the spe cific features or acts described above Rather the specific features and acts described above are disclosed as example forms of implementing the claims What is claimed is 1 A computer readable storage medium having stored thereon computer executable instructions which when executed by a computer cause the computer to collect opinion data about one or more objects from the Internet extract metadata about the opinion data from the opinion data remove duplicate metadata from the metadata to generate a resulting metadata categorize the resulting metadata for similar objects according to one or more taxonomies from one or more websites on the Internet and rank the similar objects based on the categorized metadata 2 The computer readable storage medium of claim 1 wherein the computer executable instructions which when executed by the computer cause the computer to collect the opinion data comprises computer executable instructions which when executed by a c
7. engine 60 may rank each product according to its recommendation score The recommendation score may be based on whether the total number of users who added a positive opinion on the Internet about the particular product is greater than the number of users who added a negative opin ion about the particular product For example suppose there are 100 reviews for product X and 10 reviews for product Y 49 percent of the reviews for product X are positive and 50 percent ofthe reviews for product Y are positive The opinion search engine 60 may determine the recommendation score based on the number of users who wrote a positive review as opposed to the percentage of the users who had a positive review for a product In the preceding example product X may have a higher recommendation score as compared to product Y because product X had a total of 49 positive reviews while product Y only had a total of 5 positive reviews Displaying Products by Dynamic Groups 0045 opinion search engine 60 may display products according to dynamic groups Here the opinion search engine 60 may filter the products according to the dynamic groups The opinion search engine 60 may filter products according to a product brand a manufacturer of the product or features of the product In one implementation the dynamic groups may be defined by a user by specifying to the opinion search engine 60 a percentage of positive reviews for a feature of the product For e
8. information for multiple products on the same graph In addi tion to determining the opinion change data for a product the opinion search engine 60 may also determine the opinion change data for features of a product Rank Opinion Data 0057 The opinion search engine 60 may also rank the opinion data that a user has added on the Internet In one implementation the opinion search engine 60 may rank the opinion data based on an overall ranking algorithm The overall ranking algorithm may consider the quality of the opinion data the authority ofthe user expressing the opinion the authority of the website from which the opinion was obtained and the like in ranking the opinion data The opinion search engine 60 may also rank opinion data based on feature ranking algorithm The feature ranking algorithm may rank the opinion data based on the same information considered by the overall ranking algorithm along with information pertain ing to how much of the opinion data is about a feature of interest The feature of interest may be defined by the user performing a search of opinion data on the opinion search engine 60 Generate Demographic Statistics of Opinion Data 0058 The opinion search engine 60 may also generate demographic statistics of the opinion data The demographic statistics may include location gender age etc of the user who added the opinion data The opinion search engine 60 may provide the demographic details ofthe opinion
9. is organized according to the new taxonomy This newly organized opinion metadata database may be referred to as a categorized opinion database For example on website A there may be a vehicle category that contains a list of car model manufactures like BMW Toyota etc as sub categories On website B there may be an automotive category that contains sub categories that are similar with those of the vehicle category of website A The opinion search engine 60 may then assume that vehicle and motive most likely correspond with a similar concept thereby resolving the inconsistencies between different cat egory taxonomies on different web pages 0033 At step 250 the opinion search engine 60 may rank or recommend products product categories and users opin ions based on the categorized opinion data as determined in step 240 In addition to ranking or recommending product categories and users opinions the opinion search engine 60 may display the product categories and users opinions according to various aspects of the corresponding categorized opinion data A few of the rank recommendation and display features ofthe opinion search engine 60 are described below Ranking Products Based on Hotness Score 0034 one implementation the opinion search engine 60 may rank the products in the categorized opinion database based on a hotness score The score may be determine
10. of information or an informa tion data type The computer application may then store the information pertaining to the opinion data in a second data base according to the information s particular category In this manner the second database may be structured according to the properties of the information 0003 The computer application may then remove dupli cative information and group similar information together In addition to removing duplicative information from the second database and group similar information together the com puter application may determine a taxonomy for the informa tion in the second database The taxonomy may refer to a classification scheme such that the information in the second database may be organized in a hierarchal structure In order to determine an appropriate taxonomy for all ofthe informa tion in the second database the computer application may examine the taxonomies of each webpage listed in the second database In one implementation the computer application may leverage each web page s link paths and site map infor mation to determine the appropriate taxonomy for all of the information in the second database After determining the appropriate taxonomies the computer application may orga nize the information pertaining to the opinion data in the second database according to the appropriate taxonomy The computer application may then use the organized information in the second database to rank prod
11. version number The opinion search engine 60 may determine that these two Mar 31 2011 reviews are similar because they pertain to the same product or object As such the opinion search engine 60 may combine or aggregate the metadata related to the two similar reviews 0032 At step 240 the opinion search engine 60 may cat egorize or organize the opinion data in the aggregated opinion metadata database according to a taxonomy of hierarchal categories In one implementation the opinion search engine 60 may determine the taxonomy of hierarchal categories by evaluating the category taxonomies of the web pages from which the opinion data in the opinion database may have been obtained In evaluating the category taxonomies of each web page the opinion search engine 60 may leverage each web page s link paths and site map information that may be hidden in source sites By leveraging each web page s link paths and site map information the opinion search engine 60 may reduce and consolidate the taxonomy of hierarchal categories of each web page and resolve the inconsistencies between the different category taxonomies of different web pages In other words the opinion search engine 60 may create a new tax onomy based on the consolidated taxonomy of hierarchal categories from the different web pages In one implementa tion after determining the new taxonomy the opinion search engine 60 may modify the opinion metadata database such that it
12. US 20110078157 1 as United States a2 Patent Application Publication Pub No US 2011 0078157 A1 Sun et al 43 Pub Date Mar 31 2011 54 OPINION SEARCH ENGINE Publication Classification 51 Int Cl G06F 17 30 2006 01 75 Inventors Jian Tao Sun Beijing CN G06F 7 00 2006 01 an ca A Peng 52y WS CL zs canus sensnence ees 707 749 u Beijing Gang Wang Beijing CN Ke Tang Beijing 57 ABSTRACT CN Zheng Chen Beijing CN A computer readable storage medium having stored thereon computer executable instructions which when executed by a computer cause the computer to implement an opinion 73 Assignee Microsoft Corporation Redmond search engine The instructions to implement an opinion WA US search engine cause the computer to collect opinion data about one or more objects from the Internet extract metadata about the opinion data from the opinion data remove dupli cate metadata from the metadata to generate a resulting meta 21 Appl No 12 568 702 data categorize the resulting metadata for similar objects according to one or more taxonomies from one or more web sites on the Internet and rank the similar objects based on the 22 Filed Sep 29 2009 categorized metadata 2 0 COLLECT OPINION DATA FROM INTERNET 1 220 EXTRACT METADATA FROM OPINION DATA 230 AGGREGATE n CATEGORIZE METADATA 240 3 2
13. by the computer cause the computer to rank the similar objects comprises computer executable instructions which when executed by a computer cause the computer to calculate one or more recommendation scores based on a volume of one or more reviews about the similar objects and one or more percentages of positive reviews about the similar objects and rank the similar objects based on the recommendation scores 14 The computer readable storage medium of claim 1 wherein the computer executable instructions which when executed by the computer cause the computer to rank the similar objects comprises computer executable instructions which when executed by a computer cause the computer to Mar 31 2011 identify one or more distinguishing features of the similar objects and rank the similar objects based on the distinguishing fea tures 15 The computer readable storage medium of claim 14 wherein the computer executable instructions which when executed by the computer cause the computer to identify the distinguishing features comprises computer executable instructions which when executed by a computer cause the computer to determine that a feature of the similar objects is distin guishing when a number of reviews pertaining to the feature exceeds a number of reviews pertaining to other features of the similar objects by a first predetermined value determine that the feature of the similar objects is distin guishing when
14. category e g object that may beofinterestto the user After receiving the specified product or product category the opinion search engine 60 may access all of web pages that are available on the Internet and determine whether each web page contains opinion data related to the specified product or product category Upon determining that the web page includes opinion data related to the specified product or product category the opinion search engine 60 may store the corresponding web page and the information on the web page in the opinion database In one implementation step 210 may be executed by an opinion data crawler module that may be part of the opinion search engine 60 Although the opinion data has been described as being related to products or product categories it should be understood that throughout this document the opinion data may refer to any opinion about any subject matter 0025 At step 220 the opinion search engine 60 may extract metadata from each webpage stored on the opinion database The metadata may include information pertaining to the opinion data on the webpage stored on the opinion database In one implementation the information pertaining to the opinion data may include a date and time in which the opinion was posted on the webpage a name or user identifi cation of the user who posted the opinion a product pertain ing to the opinion a product brand pertaining to the opinion the text of the opinion a senti
15. cuted by a machine such as a computer the machine becomes an apparatus for practicing the various technologies In the case of program code execution on programmable computers the computing device may include a processor a storage medium readable by the processor including volatile and non volatile memory and or storage elements at least one input device and at least one output device One or more programs that may implement or utilize the various technologies described herein may use an application programming interface reusable controls and the like Such programs may be imple mented in a high level procedural or object oriented program US 2011 0078157 A1 ming language to communicate with a computer system However the program s may be implemented in assembly or machine language if desired In any case the language may be a compiled or interpreted language and combined with hardware implementations 0021 FIG 2 illustrates a flow diagram of a method for implementing an opinion search engine in accordance with one or more implementations of various techniques described herein The following description of flow diagram 200 is made with reference to computing system 100 of FIG 1 in accordance with one or more implementations of various techniques described herein It should be understood that while the operational flow diagram 200 indicates a particular order of execution of the operations in some implementa tions
16. d by combining different information such as a query log a click through log review information reviewer information and item selling information The query log click through log review information reviewer information and item selling information may all be available to the opinion search engine 60 on the categorized opinion database as described in step 240 0035 The query log may refer to a number of query requests by one or more users on the Internet In one imple mentation the query log may indicate the interest level in one or more particular items The query log may be available from an Internet search engine 0036 click through log may describe the webpage links that a user may have clicked while surfing the Internet For instance after receiving Internet search results for a prod US 2011 0078157 A1 uct of interest the user may not click a link for each and every product that was returned as a search result In contrast the user may only click the search results that may be related to the products services or opinions that may be of interest to him The search results clicked by the user may be recorded on the click through log 0037 The review information may include the number of reviews or opinions that may exist for each product of interest and a trend of the number of reviews for each product of interest The opinion search engine 60 may determine the trend of the number of reviews based the frequenc
17. e computer to determine whether the metadata corresponds to one or more categories and store the metadata according to the categories 7 The computer readable storage medium of claim 6 wherein the computer executable instructions which when executed by the computer cause the computer to determine whether the metadata corresponds to the categories com US 2011 0078157 A1 prises computer executable instructions which when executed by a computer cause the computer to receive one or more key words for each category locate the key words in the metadata using a fuzzy match algorithm and assign the metadata having the key words to a correspond ing category 8 The computer readable storage medium of claim 1 wherein the computer executable instructions which when executed by the computer cause the computer to categorize metadata comprises computer executable instructions which when executed by a computer cause the computer to consolidate the taxonomies and organize the metadata according to the consolidated tax onomies 9 The computer readable storage medium of claim 8 wherein the taxonomies are consolidated by leveraging each website s one or more link paths and site map information 10 The computer readable storage medium of claim 1 wherein the computer executable instructions which when executed by the computer cause the computer to rank the similar objects comprises computer executable instructions whic
18. e whether the product includes one or more distinguishing features In one implementation the product specification for one product in a product category may indicate that the product costs sig nificantly more than the other products in the same category Here the price of the product may be described as a distin guishing feature because of the disparity between the price of the product as compared to prices of similar products Simi larly if other features provided in a product s specification differ significantly from the features of other products that fall within the same category of the product the opinion search engine 60 may determine that these differing features may be distinguishing features Query Products Based on Positive Negative Percentage in Features 0052 The opinion search engine 60 may also receive a request from a user to query products based on the positive and negative opinion percentages in features as described above In this implementation the opinion search engine 60 may evaluate the percentage of positive opinions and the percentage of negative opinions on each feature to determine whether the feature is a distinguishing feature The opinion search engine 60 may then list the products according to the products having the highest discrepancy between the percent age of positive opinions and the percentage of negative opin ions on the feature Compare Products Based on Opinions 0053 The opinion search e
19. eof In a distributed computing environment program modules may be located in both local and remote computer storage media including memory storage devices 0012 FIG 1 illustrates a schematic diagram of a comput ing system 100 in which the various technologies described herein may be incorporated and practiced Although the com puting system 100 may be a conventional desktop or a server computer as described above other computer system con figurations may be used 0013 The computing system 100 may include a central processing unit CPU 21 a system memory 22 and a system bus 23 that couples various system components including the system memory 22 to the CPU 21 Although only one CPU is US 2011 0078157 A1 illustrated in FIG 1 it should be understood that in some implementations the computing system 100 may include more than one CPU The system bus 23 may be any of several types of bus structures including a memory bus or memory controller a peripheral bus and a 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 also known as Mezzanine bus The system memory 22 may include a read only memory ROM 24 and a random access memory RAM 25 A basic input
20. h when executed by a computer cause the computer to calculate a score for each categorized metadata using a query log a click through log review information reviewer information and purchase history related to the similar objects and rank the similar objects according to the score 11 The computer readable storage medium of claim 1 wherein the computer executable instructions which when executed by the computer cause the computer to rank the similar objects comprises computer executable instructions which when executed by a computer cause the computer to combine one or more ratings for the similar objects that are listed in the categorized metadata and rank the similar objects according to the ratings 12 The computer readable storage medium of claim 1 wherein the computer executable instructions which when executed by the computer cause the computer to rank the similar objects comprises computer executable instructions which when executed by a computer cause the computer to determine whether one or more reviews about the similar objects are positive or negative estimate one or more authority values for one or more authors of the reviews and for one or more webpages where the reviews are located and rank the similar objects based on the reviews the authority values or combinations thereof 13 The computer readable storage medium of claim 1 wherein the computer executable instructions which when executed
21. he updated finite state machine to predict if an input term sequence corresponds with a brand name 0027 Upon extracting the metadata from the web pages in the opinion database the opinion search engine 60 may deter mine whether the metadata corresponds to a particular data property ofa product ontology The data properties ofa prod uct ontology may represent categories or definitions for the metadata In one implementation the opinion search engine 60 may receive a list of key words for each data property or category The opinion search engine 60 may then use a fuzzy match algorithm to locate the key words that may be listed in the metadata and assign the unstructured metadata to a cor responding data property The product ontology may provide US 2011 0078157 A1 anefficient mechanism to build an association among opinion data and their corresponding properties In one implementa tion the product ontology may be based on a universal ontol ogy model such that the raw data on any data source such as a webpage may be mapped to a corresponding data property In this manner the product ontology may provide a scalable architecture such that information from various websites and data sources may be more easily integrated by the opinion search engine 60 0028 In one implementation the product ontology may be defined by summarizing the details of product specifica tions published by manufacturer websites shopping sites review site
22. hese distinguishing features to a user In one implementation the opinion search engine 60 may iden tify the distinguishing features of a product by analyzing the number of users commenting on the feature the positive and negative opinion percentages of the user comments on the feature and a differentiation in feature level between each product falling in the same category in the categorized opin ion database 0050 In one implementation if the number of users com menting on a specific feature is large the opinion search engine 60 may determine that the specific feature is a distin guishing feature The opinion search engine 60 may also use the positive and negative opinion percentages of the user comments about the feature to determine whether a feature is distinguishable Here if the percentage of positive opinions and the percentage of negative opinions are relatively similar the opinion search engine 60 may determine that the feature Mar 31 2011 pertaining to the positive and negative opinions is not distin guishable However if there is a large difference between the percentage of positive opinions and the percentage of nega tive opinions pertaining to the product feature the opinion search engine 60 may determine that the product feature is a distinguishing feature 0051 The opinion search engine 60 may also use other information pertaining to the product such as specification information about the product to determin
23. hown in FIG 3 FIG 3 illustrates the trend oftheopinion data over a time period of one year As such the total number of opinions for each month during one year is illustrated on the graph 300 The trend of the total number of opinions represented by the line 310 In addition to displaying the trend ofthe opinion data for a single product the opinion search engine 60 may compare the trend of the opinion data over a period of time for multiple products In this manner the opinion data trend for each of the multiple products may be represented by different lines on a graph similar to that as illustrated in FIG 3 View Opinion Change Data 0056 The opinion search engine 60 may determine the volume of change in the number of user comments for a product the number of positive comments for a product the number of negative comments for a product the percentage of user comments for a product the percentage of positive com ments for a product the percentage of negative comments for a product and the like The opinion search engine 60 may determine the change with respect to a time period e g week month as defined by a user After determining the change in the various types of comments for a product the opinion search engine 60 may display the opinion change data to the user FIG 4 illustrates the opinion data change in volume and percentage from Month 1 to Month 2 The opin ion search engine 60 may also display the opinion data change
24. in the memory further comprises program instructions executable by the at least one processor to display a change in a number reviews for the similar objects over a time period 19 The computer system of claim 16 wherein the memory further comprises program instructions executable by the at least one processor to recommend one or more related objects having similar properties features components or combina tions thereof as the similar objects 20 method for creating an opinion search engine com prising collecting opinion data about one or more objects from the Internet extracting metadata about the opinion data from the opin ion data US 2011 0078157 A1 Mar 31 2011 removing duplicate metadata from the metadata to gener ranking using a microprocessor the opinion data about the ate a resulting metadata one of the objects based on a quality of one or more reviews one or more authority values of one or more authors of the reviews and one or more webpages from which the reviews exist categorizing resulting metadata for similar objects accord ing to one or more taxonomies from one or more web sites on the Internet receiving one of the objects and EE E E E
25. ment polarity of the opinion or any other subject matter pertaining to the opinion The opin ion search engine 60 may determine a product s brand name by using a finite state machine 0026 In order to determine a product s brand name using a finite state machine the opinion search engine 60 may use a word breaker to generate or create a sequence of terms contained in a product name as it is listed on a web page Given a finite state machine having states and transitions represented by terms and grammar and an input term sequence e g product that is not accepted by the finite state machine the opinion search engine 60 may use an algorithm to find a minimal set of modifications that may be made to the finite state machine such that the input term sequence is acceptable In one implementation the opinion search engine 60 may run the algorithm iteratively and update the finite state machine such that it contains the input term sequence The opinion search engine 60 may update the finite state machine through induction such that the transition represented by the terms may be changed into transitions represented by gram mar and new transitions and new states may be added to the finite state machine ifthey were not previously represented on the finite state machine The output of algorithm 15 a finite state machine consisting of multiple state sequences such that each state sequence is a product name The opinion search engine 60 may then use t
26. nections may be any connection that is commonplace in offices enterprise wide computer networks intranets and the Internet such as local area network LAN 51 and a wide area network WAN 52 0019 When using a LAN networking environment the computing system 100 may be connected to the local network 51 through a network interface or adapter 53 When used in a WAN networking environment the computing system 100 may include a modem 54 wireless router or other means for establishing communication over a wide area network 52 such as the Internet The modem 54 which may be internal or external may be connected to the system bus 23 via the serial port interface 46 In a networked environment program mod ules depicted relative to the computing system 100 or por tions thereof may be stored in a remote memory storage device 50 It will be appreciated that the network connections shown are exemplary and other means of establishing a com munications link between the computers may be used 0020 It should be understood that the various technolo gies described herein may be implemented in connection with hardware software or a combination of both Thus various technologies or certain aspects or portions thereof may take the form of program code 1 instructions embodied in tangible media such as floppy diskettes CD ROMs hard drives or any other machine readable storage medium wherein when the program code is loaded into and exe
27. ngine 60 may also display a comparison between two or more products The comparison between the products may compare the distinguishing fea tures between the two or more products The opinion search engine 60 may identify the distinguishing features according to the method for identifying distinguishing features of a product as described above Display and Compare Opinion Trend 0054 The opinion search engine 60 may also organize opinion data according its trend Here the opinion search engine 60 may evaluate the trend of the opinion data or reviews for a particular product or a product feature over a period of time In one implementation if the number of opin ions pertaining to the product or the product feature is increas ing the opinion search engine 60 may display an arrow point ing up next to the corresponding product or product feature to indicate that the trend for the corresponding opinion data about the product or product feature is rising If however the number of opinions pertaining to the product or the product feature is decreasing the opinion search engine 60 may dis play an arrow pointing down next to the corresponding prod uct or product feature to indicate that the trend for the corre sponding opinion data about the product or product feature is falling US 2011 0078157 A1 0055 The opinion search engine 60 may also display the trend ofthe opinion data for a single product over a period of time on a graph as s
28. omputer cause the computer to access one or more webpages on the Internet determine whether the webpages contain the opinion data and store the webpages containing the opinion data in a data base 3 The computer readable storage medium of claim 1 wherein the computer executable instructions which when executed by the computer cause the computer to collect the opinion data comprises computer executable instructions which when executed by a computer cause the computer to receive a description of the objects access one or more webpages on the Internet determine whether the webpages contain the opinion data about the objects and store the webpages containing the opinion data about the objects in a database 4 The computer readable storage medium of claim 1 wherein the objects comprise one or more products one or more product categories vacation locations reviews or any subject matter of interest 5 The computer readable storage medium of claim 1 wherein the metadata comprises a date and a time of the opinion data an author of the opinion data a rating of the objects a sentiment polarity of the objects a review of the objects or combinations thereof 6 The computer readable storage medium of claim 1 wherein the computer executable instructions which when executed by the computer cause the computer to extract the metadata comprises computer executable instructions which when executed by a computer cause th
29. output system BIOS 26 containing the basic routines that help transfer information between elements within the com puting system 100 such as during start up may be stored in the ROM 24 0014 The computing system 100 may further include a hard disk drive 27 for reading from and writing to a hard disk a magnetic disk drive 28 for reading from and writing to a removable magnetic disk 29 and an optical disk drive 30 for reading from and writing to a removable optical disk 31 such as a CD ROM or other optical media The hard disk drive 27 the magnetic disk drive 28 and the optical disk drive 30 may be connected to the system bus 23 by a hard disk drive inter face 32 a magnetic disk drive interface 33 and an optical drive interface 34 respectively The drives and their associ ated computer readable media may provide nonvolatile stor age of computer readable instructions data structures pro gram modules and other data for the computing system 100 0015 Although the computing system 100 is described herein as having a hard disk a removable magnetic disk 29 and a removable optical disk 31 it should be appreciated by those skilled in the art that the computing system 100 may also include other types of computer readable media that may be accessed by a computer For example such computer readable media may include computer storage media and communication media Computer storage media may include volatile and non volatile and remo
30. pinion search engine Various techniques for implementing an opinion search engine will be described in more detail with reference to FIGS 1 4 0010 Implementations of various technologies described herein may be operational with numerous general purpose or special purpose computing system environments or configu rations Examples of well known computing systems envi ronments and or configurations that may be suitable for use with the various technologies described herein include but are not limited to personal computers server computers hand held or laptop devices multiprocessor systems micro processor based systems set top boxes programmable con sumer electronics network PCs minicomputers mainframe computers distributed computing environments that include any of the above systems or devices and the like 0011 The various technologies described herein may be implemented in the general context of computer executable instructions such as program modules being executed by a computer Generally program modules include routines pro grams objects components data structures etc that per forms particular tasks or implement particular abstract data types The various technologies described herein may also be implemented in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network e g by hardwired links wireless links or combinations ther
31. r based on whether the user is an editor on the website a product specialist or the like 0042 In another implementation various websites may provide a rating for each user In this case the opinion search engine 60 may estimate the authority of each user based on the rating provided by the website If the opinion search engine 60 determines that an opinion has been added from a user with a higher authority the opinion search engine 60 may give that user s opinion more weight in determining the uni fied opinion score In addition to estimating the authority of each user the opinion search engine 60 may also estimate the authority of each website containing user opinions 0043 The opinion search engine 60 may also evaluate the review provided by a user in order to calculate an opinion score Here the opinion search engine 60 may analyze the review provided by the user and determine whether the review includes characteristics that indicate that it is a positive review about the product or a negative review about the prod uct Rank Products Based on a Recommendation Score 0044 The opinion search engine 60 may also rank the products according to a recommendation score The opinion search engine 60 may calculate the recommendation score based on the volume of the opinions or reviews provided for a particular product and the percentage of positive opinions or reviews related to the particular product In this manner the opinion search
32. r may be accessible via the Internet The opinion database may be stored on the database system 55 as described in FIG 1 0023 In one implementation in order to determine whether the web page contains opinion data the opinion search engine 60 may check how many opinion words are contained in a web page If the number of opinion words exceeds a predefined threshold the opinion search engine 60 may describe the web page as having opinion data Opinion words may include words that are usually used to express opinions e g good exciting and bad In one imple mentation the opinion words may be manually provided by both human editors and machine learning algorithms In prac tical applications machines may be used to generate opinion words and then human editors may manually check or filter them in order to ensure the quality of the opinion words Although web pages having opinion data have been described as being identified by determining how many opinion words are contained in the web pages it should be noted that in other implementations various algorithms may be used to deter mine whether the opinion data is contained on the web pages 0024 In another implementation the opinion search engine 60 may collect only targeted or specific opinion data from the Internet as opposed to all of the opinion data avail able on the Internet In this implementation a user may Mar 31 2011 specify a particular product or product
33. real time while the user is online In other implementations the opinion search engine 60 may compute the hotness scores for each product while the user is offline using the informa tion previously obtained from the users on the Internet Rank Products by User Opinion 0040 In yet another implementation the opinion search engine 60 may rank the products according to the users opinions or an opinion score about the product In order to rank the products according to the users opinions about the product the opinion search engine 60 may evaluate the rat ings and the ranking of various products as provided on various websites For instance on some shopping websites products may be ranked based on average rating scores pro vided by Internet users Since each shopping website may employ its own rating system the opinion search engine 60 may combine the ratings for a product from each website to determine a unified opinion score for each product 0041 The opinion search engine 60 may calculate the unified opinion score based on a total number of users writing a review about a product the rating score of each user if a rating score is available whether the review is positive or negative if a rating score is unavailable an authority estimate for each user an authority estimate for each website contain ing user reviews and the like In one implementation the Mar 31 2011 opinion search engine 60 estimate the authority of each use
34. s and other related data sources The ontology may be defined in OWL a standard ontology language published by the World Wide Web Consortium W3C OWL may facili tate a greater machine interpretability of Web content than that supported by Extensible Markup Language XML Resource Description Framework RDF RDF Schema RDFS DARPA Agent Markup Language DAML by viding additional vocabulary along with a formal semantics Depending on the extensibility of OWL the product ontology definition may be extended with additional ontology prop erty and relationship definition 0029 After identifying the keywords related to the meta data on each webpage the opinion search engine 60 may store the metadata of the opinion data in an opinion metadata database In one implementation the opinion metadata data base may be structured in a manner such that the information pertaining to the opinion data may be easily queried The opinion metadata database may be structured according to the data properties of the product ontology For example the metadata database may store information pertaining to the opinion data in a spreadsheet such that each column of the spreadsheet may define a different property of the opinion data In one implementation the text information reciting a user s review or opinion of a product may not be stored in a structured format since the text provided by each user may differ greatly and may not be easily queried
35. ss their opinion about any topic of interest such books hotels con sumer products political policy and the like These opinions about various topics of interest may be referred to as opinion data Opinion data is typically used to help consumers make an informed purchase decision about an item that they may wish to purchase based on the opinions of other consumers Opinion data is also used to help companies learn more about how their customers rate their products customer sentiment fortheir products and customer satisfaction for their products Since anyone can add an opinion about anything on the Inter net opinion data is voluminous and includes a plethora of diverse topics which makes it difficult for users to locate relevant opinions related to their topic of interest SUMMARY 0002 Described herein are implementations of various technologies for implementing an opinion search engine In one implementation a computer application may access each webpage available on the Internet and determine whether each webpage contains opinion data If the webpage contains opinion data the computer application may store the webpage on a first database The computer application may then extract information pertaining to the opinion data from each webpage stored on the first database While extracting the information pertaining to the opinion data the computer application may determine whether the information corre sponds to a particular category
36. tored on the hard disk 27 magnetic disk 29 optical disk 31 ROM 24 or RAM 25 including an operating system 35 one or more application programs 36 an opinion search engine 60 pro gram data 38 and a database system 55 The operating system 35 may be any suitable operating system that may control the operation ofa networked personal or server computer such as Windows XP Mac OS X Unix variants e g Linux and BSD and the like The opinion search engine 60 will be described in more detail with reference to FIG 2 in the paragraphs below 0017 user may enter commands and information into the computing system 100 through input devices such as a keyboard 40 and pointing device 42 Other input devices may include a microphone joystick game pad satellite dish scanner or the like These and other input devices may be connected to the CPU 21 through a serial port interface 46 coupled to system bus 23 but may be connected by other interfaces such as a parallel port game port or a universal serial bus USB A monitor 47 or other type of display device may also be connected to system bus 23 via an interface such as a video adapter 48 In addition to the monitor 47 the computing system 100 may further include other peripheral output devices such as speakers and printers 0018 Further the computing system 100 may operate networked environment using logical connections to one or more remote computers 49 The logical con
37. ucts product categories opinions and other opinion related subject matter on the Internet 0004 above referenced summary section is provided to introduce a selection of concepts in a simplified form that are further described below in the detailed description sec tion The summary is not intended to identify key features or Mar 31 2011 essential features of the claimed subject matter nor is it intended to be used to limit the scope of the claimed subject matter Furthermore the claimed subject matter is not limited to implementations that solve any or all disadvantages noted in any part of this disclosure BRIEF DESCRIPTION OF THE DRAWINGS 0005 FIG 1 illustrates a schematic diagram of a comput ing system in which the various techniques described herein may be incorporated and practiced 0006 FIG 2 illustrates a flow diagram of a method for implementing an opinion search engine in accordance with one or more implementations of various techniques described herein 0007 FIG 3 illustrates a graph of a trend of opinion data for a single product in accordance with one or more imple mentations of various techniques described herein 0008 FIG 4 illustrates graphs of opinion change data for a single product in accordance with one or more implemen tations of various techniques described herein DETAILED DESCRIPTION 0009 In general one or more implementations described hereinare directed to implementing an o
38. vable and non removable media implemented in any method or technology for storage of information such as computer readable instructions data structures program modules or other data Computer storage media may further include RAM ROM erasable program mable read only memory EPROM electrically erasable programmable read only memory EEPROM flash memory or other solid state memory technology CD ROM digital versatile disks DVD or other optical storage magnetic cassettes magnetic tape magnetic disk storage or other mag netic storage devices or any other medium which can be used to store the desired information and which can be accessed by the computing system 100 Communication media may embody computer readable instructions data structures pro gram modules or other data in a modulated data signal such as a carrier wave or other transport mechanism and may include any information delivery media The term modu lated data signal may mean a signal that has one or more of its characteristics set or changed in such a manner as to encode information in the signal By way of example and not limitation communication media may include wired media such as a wired network or direct wired connection and wireless media such as acoustic RF infrared and other wire less media Combinations of any of the above may also be included within the scope of computer readable media Mar 31 2011 0016 Anumber of program modules may be s
39. xample a product may include features such as a user manual noise resolution and weight The opinion search engine 60 may display a window to the user such that the user may specify how to filter the products in the categorized opinion database The user may specify a percentage of positive reviews for each feature ofthe product In one implementation the user may be interested in a prod uct having high ratings for its user manual As such the user may specify to the opinion search engine 60 that the percent US 2011 0078157 A1 age of positive reviews pertaining to the product s user manual will be 7096 or greater Accordingly the opinion search engine 60 may remove all of the products having less than 7096 positive reviews for its manual In one implemen tation the opinion search engine 60 may determine whether the reviews for each feature of a product include positive or negative reviews based on a calculated opinion score as described above Recommending Related Products 0046 The opinion search engine 60 may also identify products that are related to each other The related products may have similar properties features and or components For example different products may use a similar memory device in order to store information i e SD memory card In this example the different products using similar memory devices may be associated with each other as related prod ucts As such the opinion search engine 60 may associate
40. y of the addition of new reviews over a period of time For example if two opinions were added in month 1 for product X and ten opinions were added in month 2 for product X the opinion search engine 60 may determine that the trend is rising because more reviews are being added with respect to time The opinion search engine 60 may also distinguish the trend data according to positive opinion trends negative opinion trends and the like 0038 The reviewer information may describe the user who adds opinions on the Internet The reviewer information may include the number of reviewers commenting or adding an opinion for a product the demographic information per taining to the user e g gender age and location coverage of user and the like 0039 selling information may describe the num ber of products that have been sold to or purchased by the users The opinion search engine 60 may then determine a hotness score for the product reviewed by the users based on the query log click through log review information reviewer information and item selling information Based on the hotness score for the various products reviewed by the users the opinion search engine 60 may also rank product categories according to a hotness score that may be computed based on the hotness scores of all of the products in each product category In one implementation the opinion search engine 60 may compute the hotness scores for each product in

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