information presented to a user via an information access system is ranked according to a prediction of the likely degree of relevance to the user's interests. A profile of interests is stored for each user having access to the system. items of information to be presented to a user are ranked according to their likely degree of relevance to that user and displayed in order of ranking. The prediction of relevance is carried out by combining data pertaining to the content of each item of information with other data regarding correlations of interests between users. A value indicative of the content of a document can be added to another value which defines user correlation, to produce a ranking score for a document. Alternatively, multiple regression analysis or evolutionary programming can be carried out with respect to various factors pertaining to document content and user correlation, to generate a prediction of relevance. The user correlation data is obtained from feedback information provided by users when they retrieve items of information. Preferably, the user provides an indication of interest in each document which he or she retrieves from the system.
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28. A method for displaying items of information to users, comprising the steps of:
determining a relevance factor for an item of information, based upon an attribute of the item of information;
defining a relationship between the interests of a given user and those of other users;
determining a correlation factor for the item of information, based upon said defined relationship;
combining said relevance factor and said correlation factor to produce a ranking score for the item of information; and
displaying the item of information to the given user in accordance with its ranking score.
0. 102. A method of presenting information items from an information item collection to a user, the method comprising:
accessing a user profile associated with the user;
for each information item in the information item collection:
determining a relevance score for the information item based on a relationship between the user profile and the information item; and
determining a correlation score between the user and other users corresponding to the information item; and
ranking the information items based on a combination of each information item's relevance score and correlation score for presentation to the user.
14. A computer-based information access system, comprising:
a first database containing items of information to be provided to users of said system;
means for enabling users to indicate their degree of interest in particular items of information stored in said first database;
means for determining the correlation between the indicated interests of respective users and for storing information related thereto; and
means for predicting a given user's likely degree of interest in a particular item of information on the basis of said information relating to the determined correlation and at least one attribute of the item of information.
0. 103. A computer program product for presenting information items from an information item collection to a user, the computer program product stored on a computer readable medium and configured to perform a method comprising:
accessing a user profile associated with the user;
for each information item in the information item collection:
determining a relevance score for the information item based on a relationship between the user profile and the information item; and
determining a correlation score between the user and other users corresponding to the information item; and
ranking the information items based on a combination of each information item's relevance score and correlation score for presentation to the user.
0. 72. A method of presenting documents received from a document collection to a user, the method comprising:
retrieving a user profile vector associated with the user, the user profile vector in a vector space derived from terms in the document collection;
receiving a plurality of documents from the document collection, each document having a document vector in the vector space;
for each received document:
determining a relevance score for the document by a vector operation comparing the user profile vector and the document vector; and
determining a correlation score between the user and other users corresponding to the document; and
ranking the received documents based on a combination of each received document's relevance score and correlation score for presentation to the user.
0. 104. A system for presenting information items to a user, the information items stored in an information item database coupled to the system, the system comprising:
a user database storing a user profile associated with the user;
a server coupled to the information item database and the user database, the server identifying information items from the information item database and determining a relevance score for each of the identified information items based on a relationship between the user profile and the information item and determining a correlation score for each of the identified information items between the user and other users corresponding to the information item and ranking the identified information items based on a combination of each identified information item's relevance score and correlation score for presentation to the user.
0. 70. A method comprising:
storing a user profile for a user, the user profile including terms contained in a document collection and weights respectively associated with the terms;
selecting a plurality of documents from the document collection, each document associated with a document profile, the document profile including terms contained in its associated document;
for each selected document:
determining a relevance score, the relevance score based on a relationship between the user profile and the document profile associated with the selected document;
determining a correlation score between the user and other users corresponding to the selected document; and
combining the relevance score and the correlation score to determine a final ranking score for the selected document; and
presenting one or more recommendations to the user based on the final ranking scores.
0. 82. A computer program product for presenting documents received from a document collection to a user, the computer program product stored on a computer readable medium and configured to perform a method comprising:
retrieving a user profile vector associated with the user, the user profile vector in a vector space derived from terms in the document collection;
receiving a plurality of documents from the document collection, each document having a document vector in the vector space;
for each received document:
determining a relevance score for the document by a vector operation comparing the user profile vector and the document vector; and
determining a correlation score between the user and other users corresponding to the document; and
ranking the received documents based on a combination of each received document's relevance score and correlation score for presentation to the user.
0. 92. A system for presenting documents to a user, the documents each having a document vector in a vector space and stored in a document database coupled to the system, the system comprising:
a user database storing a user profile vector associated with the user, the user profile vector in the vector space derived from terms in the document database;
a server coupled to the document database and the user database, the server receiving documents from the document database and determining a relevance score for each of the received documents by a vector operation comparing the user profile vector and the document vector and determining a correlation score for each of the received documents between the user and other users corresponding to the document and ranking the received documents based on a combination of each received document's relevance score and correlation score for presentation to the user.
0. 67. A method of presenting documents from a document collection to a user, the method comprising:
storing a user profile for the user, the user profile including terms contained in the document collection and weights respectively associated with the terms;
selecting a plurality of documents from the document collection, each document associated with a document profile, the document profile including terms contained in its associated document;
for each selected document:
determining a relevance score, the relevance score based on a relationship between the user profile and the document profile associated with the selected document;
determining a correlation score between the user and other users corresponding to the selected document; and
combining the relevance score and the correlation score to determine a final ranking score for the selected document; and
presenting the selected documents to the user according to the final ranking scores.
1. In a computerized information access system, a method for presenting items of information to users, comprising the steps of:
a) storing user profiles for users having access to the system, where each user profile is based, at least in part, on the attributes of information the user finds to be of interest;
b) determining an attribute-based relevance factor for an item of information which is indicative of the degree to which an attribute of that item of information matches the profile for a particular user;
c) determining a measure of correlation between the particular user's interests and those of other users who have accessed said item of information;
d) combining said relevance factor and said degree of correlation to produce a ranking score for said item of information;
e) repeating steps b, c and d for each item of information to be presented to said particular user; and
f) displaying the items of information to the user in accordance with their ranking scores.
0. 31. A method of presenting documents from a document collection to a user, the method comprising:
storing a user profile vector for the user, the user profile vector in a vector space derived from terms contained in the document collection and including a plurality of weights, each weight associated with a term in the document collection;
selecting a plurality of documents from the document collection, each document associated with a document vector in the term vector space;
for each selected document:
determining a relevance score, the relevance score based on a relationship between the user profile vector and the document vector associated with the selected document;
determining a correlation score between the user and other users corresponding to the selected document; and
combining the relevance score and the correlation score to determine a final ranking score for the selected document; and
presenting the selected documents to the user according to the final ranking scores.
0. 37. A computer program product for presenting documents from a document collection to a user, the computer program product stored on a computer readable medium and adapted to perform a method comprising:
storing a user profile vector for the user, the user profile vector in a vector space derived from terms contained in the document collection and including a plurality of weights, each weight associated with a term in the document collection;
selecting a plurality of documents from the document collection, each document associated with a document vector in the term vector space;
for each selected document:
determining a relevance score, the relevance score based on a relationship between the user profile vector and the document vector associated with the selected document;
determining a correlation score between the user and other users corresponding to the selected document; and
combining the relevance score and the correlation score to determine a final ranking score for the selected document; and
presenting the selected documents to the user according to the final ranking scores.
0. 49. A method of presenting information items from an information item collection to a user, the method comprising:
storing a user profile vector for the user, the user profile vector in a vector space derived from attributes in the information item collection and including a plurality of weights, each weight associated with an attribute in the information item collection;
selecting a plurality of information items from the information item collection, each information item associated with an information item vector in the attribute vector space;
for each selected information item:
determining a relevance score, the relevance score based on a relationship between the user profile vector and the information item vector associated with the selected information item;
determining a correlation score between the user and other users corresponding to the selected information item; and
combining the relevance score and the correlation score to determine a final ranking score for the selected information item; and
presenting the selected information items to the user according to the final ranking scores.
0. 43. A system for presenting documents to a user, the documents each associated with a document vector in a vector space and stored in a document database coupled to the system, the system comprising:
a user database storing a user profile vector for the user, the user profile vector in the vector space derived from terms contained in the document database and including a plurality of weights, each weight associated with a term in the document collection; and
a server coupled to the user database and the document database for selecting documents from the document database, wherein the server:
determines, for each selected document, a relevance score, the relevance score based on a relationship between the user profile vector and the document vector associated with the selected document;
determines, for each selected document, a correlation score between the user and other users corresponding to the selected document;
combines, for each selected document, the relevance score and the correlation score to determine a final ranking score for the selected document; and
presents the selected documents to the user according to the final ranking scores.
0. 55. A computer program product for presenting information items from an information item collection to a user, the computer program product stored on a computer readable medium and adapted to perform a method comprising:
storing a user profile vector for the user, the user profile vector in a vector space derived from attributes contained in the information item collection and including a plurality of weights, each weight associated with an attribute in the information item collection;
selecting a plurality of information items from the information item collection, each information item associated with an information item vector in the attribute vector space;
for each selected information item:
determining a relevance score, the relevance score based on a relationship between the user profile vector and the information item vector associated with the selected information item;
determining a correlation score between the user and other users corresponding to the selected information item; and
combining the relevance score and the correlation score to determine a final ranking score for the selected information item; and
presenting the selected information items to the user according to the final ranking scores.
0. 61. A system for presenting information items to a user, the information items each associated with an information item vector in the attribute vector space and stored in an information item database coupled to the system, the system comprising:
a user database storing a user profile vector for the user, the user profile vector in a vector space derived from attributes contained in the information item database and including a plurality of weights, each weight associated with an attribute in the information item collection; and
a server coupled to the user database and the information item database for selecting information items from the information item database, wherein the server:
determines, for each selected information item, a relevance score, the relevance score based on a relationship between the user profile vector and the information item vector associated with the selected information item;
determines, for each selected information item, a correlation score between the user and other users corresponding to the selected information item;
combines, for each selected information item, the relevance score and the correlation score to determine a final ranking score for the selected information item; and
presents the selected information items to the user according to the final ranking scores.
2. The method of
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9. The method of
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12. The method of
13. The method of
15. The information access system of
16. The information access system of
17. The information access system of
18. The information access system of
19. The information access system of
20. The information access system of
21. The information access system of
22. The information access system of
23. The information access system of
24. The system of
25. The system of
26. The system of
27. The method of
29. The method of
30. The method of
0. 32. The method of
storing information relating to users' interest in the documents in the document collection;
storing information relating to the degree of correlation between the users' interest in documents;
generating the correlation score based upon the information relating to the users' interest and the information relating to the degree of correlation.
0. 33. The method of
the information relating to the users' interests in the documents is stored in a user interest matrix indicating the users' interests in particular documents;
the degree of correlation between the users' interest is stored in a correlation matrix indicating the degree of correlation between the users' interest in the documents; and
the correlation score is generated based upon the user interest matrix and the correlation matrix.
0. 34. The method of
storing information relating to the users' interest comprises generating a user interest matrix V where each entry Vkj is the weight indicating the feedback of user k on document j;
storing information relating to the degree of correlation comprises generating a correlation matrix R where each entry Rjk is a measure of the degree of correlation between users i and k; and
generating the correlation score comprises calculating a prediction score Pij indicating a likelihood of user i's interest in document j by carrying out an operation,
0. 35. The method of
0. 36. The method of
0. 38. The computer program product of
storing information relating to users' interest in the documents in the document collection;
storing information relating to the degree of correlation between the users' interest in documents;
generating the correlation score based upon the information relating to the users' interest and the information relating to the degree of correlation.
0. 39. The computer program product of
the information relating to the users' interests in the documents is stored in a user interest matrix indicating the users' interests in particular documents;
the degree of correlation between the users' interest is stored in a correlation matrix indicating the degree of correlation between the users' interest in the documents; and
the correlation score is generated based upon the user interest matrix and the correlation matrix.
0. 40. The computer program product of
storing information relating to the users' interest comprises generating a user interest matrix V where each entry Vkj is the weight indicating the feedback of user k on document j;
storing information relating to the degree of correlation comprises generating a correlation matrix R where each entry Rjk is a measure of the degree of correlation between users i and k; and
generating the correlation score comprises calculating a prediction score Pij indicating a likelihood of user i's interest in document j by carrying out an operation,
0. 41. The computer program product of
0. 42. The computer program product of
0. 44. The system of
storing information relating to users' interest in the documents in the document collection;
storing information relating to the degree of correlation between the users' interest in documents;
generating the correlation score based upon the information relating to the users' interest and the information relating to the degree of correlation.
0. 45. The system of
the information relating to the users' interests in the documents is stored in a user interest matrix indicating the users' interests in particular documents;
the degree of correlation between the users' interest is stored in a correlation matrix indicating the degree of correlation between the users' interest in the documents; and
the server generates the correlation score based upon the user interest matrix and the correlation matrix.
0. 46. The system of
the information relating to the users' interest is stored in a user interest matrix V where each entry Vkj is the weight indicating the feedback of user k on document j;
the information relating to the degree of correlation is stored in a correlation matrix R where each entry Rjk is a measure of the degree of correlation between users i and k; and
the server generates the correlation score by calculating a prediction score Pij indicating a likelihood of user i's interest in document j by carrying out an operation,
0. 47. The system of
0. 48. The method of
0. 50. The method of
storing information relating to users' interest in the information items in the information item collection;
storing information relating to the degree of correlation between the users' interest in information items;
generating the correlation score based upon the information relating to the users' interest and the information relating to the degree of correlation.
0. 51. The method of
the information relating to the users' interests in the information items is stored in a user interest matrix indicating the users' interests in particular information items;
the degree of correlation between the users' interest is stored in a correlation matrix indicating the degree of correlation between the users' interest in the information items; and
the correlation score is generated based upon the user interest matrix and the correlation matrix.
0. 52. The method of
storing information relating to the users' interest comprises generating a user interest matrix V where each entry Vkj is the weight indicating the feedback of user k on information item j;
storing information relating to the degree of correlation comprises generating a correlation matrix R where each entry Rik is a measure of the degree of correlation between users i and k; and
generating the correlation score comprises calculating a prediction score Pij indicating a likelihood of user i's interest in information item j by carrying out an operation,
0. 53. The method of
0. 54. The method of
0. 56. The computer program product of
storing information relating to users' interest in the information items in the information item collection;
storing information relating to the degree of correlation between the users' interest in information items;
generating the correlation score based upon the information relating to the users' interest and the information relating to the degree of correlation.
0. 57. The computer program product of
the information relating to the users' interests in the information items is stored in a user interest matrix indicating the users' interests in particular information items;
the degree of correlation between the users' interest is stored in a correlation matrix indicating the degree of correlation between the users' interest in the information items; and
the correlation score is generated based upon the user interest matrix and the correlation matrix.
0. 58. The computer program product of
storing information relating to the users' interest comprises generating a user interest matrix V where each entry Vkj is the weight indicating the feedback of user k on information item j;
storing information relating to the degree of correlation comprises generating a correlation matrix R where each entry Rjk is a measure of the degree of correlation between users i and k; and
generating the correlation score comprises calculating a prediction score Pij indicating a likelihood of user i's interest in information item j by carrying out an operation,
0. 59. The computer program product of
0. 60. The computer program product of
0. 62. The system of
storing information relating to users' interest in the information items in the information item collection;
storing information relating to the degree of correlation between the users' interest in information items;
generating the correlation score based upon the information relating to the users' interest and the information relating to the degree of correlation.
0. 63. The system of
the information relating to the users' interests in the information items is stored in a user interest matrix indicating the users' interests in particular information items;
the degree of correlation between the users' interest is stored in a correlation matrix indicating the degree of correlation between the users' interest in the information items; and
the server generates the correlation score based upon the user interest matrix and the correlation matrix.
0. 64. The system of
the information relating to the users' interest is stored in a user interest matrix V where each entry Vkj is the weight indicating the feedback of user k on information item j;
the information relating to the degree of correlation is stored in a correlation matrix R where each entry Rik is a measure of the degree of correlation between users i and k; and
the server generates the correlation score by calculating a prediction score Pij indicating a likelihood of user i's interest in information item j by carrying out an operation,
0. 65. The server of
0. 66. The server of
0. 68. The method of
0. 69. The method of
0. 71. The method of
0. 73. The method of
0. 74. The method of
0. 75. The method of
0. 76. The method of
0. 77. The method of
0. 78. The method of
receiving a user rating of a document;
responsive to positive user rating, modifying the user profile vector of the user so that the user profile vector is more similar to the document vector of the user rated document; and
responsive to a negative user rating, modifying the user profile vector of the user so that the user profile vector is less similar to the document vector of the user rated document.
0. 79. The method of
receiving a user rating of a document; and
modifying the user profile vector as a function of the user rating and the document vector of the user rated document.
0. 80. The method of
receiving a user rating of a document indicating a user interest in the user rated document; and
modifying the user profile vector by determining which terms of the user rated document are significant and increasing the weights corresponding to the significant terms in the user profile vector.
0. 81. The method of
updating the first user profile vector in response to a user rating of a document from the first document database; and
updating the second user profile vector in response to a user rating of a document from the second document database.
0. 83. The computer program product of
0. 84. The computer program product of
0. 85. The computer program product of
0. 86. The computer program product of
0. 87. The computer program product of
0. 88. The computer program product of
receiving a user rating of a document;
responsive to positive user rating, modifying the user profile vector of the user so that the user profile vector is more similar to the document vector of the user rated document; and
responsive to a negative user rating, modifying the user profile vector of the user so that the user profile vector is less similar to the document vector of the user rated document.
0. 89. The computer program product of
receiving a user rating of a document; and
modifying the user profile vector as a function of the user rating and the document vector of the user rated document.
0. 90. The computer program product of
receiving a user rating of a document indicating a user interest in the user rated document; and
modifying the user profile vector by determining which terms of the user rated document are significant and increasing the weights corresponding to the significant terms in the user profile vector.
0. 91. The computer program product of
updating the first user profile vector in response to a user rating of a document from the first document database; and
updating the second user profile vector in response to a user rating of a document from the second document database.
0. 93. The system of
0. 94. The system of
0. 95. The system of
0. 96. The system of
0. 97. The system of
0. 98. The system of
responsive to positive user rating, modifies the user profile vector of the user so that the user profile vector is more similar to the document vector of the user rated document; and
responsive to a negative user rating, modifies the user profile vector of the user so that the user profile vector is less similar to the document vector of the user rated document.
0. 99. The system of
0. 100. The system of
0. 101. The system of
updates the first user profile vector in response to a user rating of a document from the first document database; and
updates the second user profile vector in response to a user rating of a document from the second document database.
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In this formula, each parenthetical product pertains to one of the other users, i.e., A, B and D, respectively. Within each product, the first value represents the degree of correlation between the other user and the current user in question, as indicated by the matrix 44. The second value indicates whether the other user voted favorably (+1) or negatively (−1) after reading the document, as indicated in the table 42. The values of +1 and −1 are merely exemplary. Any suitable range of values can be employed to indicate various users' interests in retrieved items of information.
In accordance with the invention, a combination of attribute-based and correlation-based prediction is employed to rank the relevance of each item of information. For example, a weighted sum of scores that are obtained from each of the content and correlation predictors can be used, to determine a final ranking score. Other approaches which take into account both the attribute-based information and user correlation information can be employed. For example, multiple regression analysis can be utilized to combine the various factors. In this approach, regression methods are employed to identify the most important attributes that are used as predictors, e.g., salient terms in a document and users having similar feedback responses, and how much each one should be weighted. Alternatively, principal components analysis can be used to identify underlying aspects of content-based and correlation-based data that predict a score.
As another example, evolutionary programming techniques can be employed to analyze the available data regarding content of messages and user correlations. One type of evolutionary programming that is suitable in this regard is known as genetic programming. In this type of programming, data pertaining to the attributes of messages and user correlation are provided as a set of primitives. The various types of data are combined in different manners and evaluated, until the combination which best fits known results is found. The result of this combination is a program that describes the data which can best be used to predict a given user's likely degree of interest in a message. For further information regarding genetic programming, reference is made to Koza, John R., Genetic Programming: On The Programming of Computers By Means of Natural Selection, MIT Press 1992.
In a more specific implementation of evolutionary programming, the analysis technique known as genetic algorithms can be employed. This technique differs from genetic programming by virtue of the fact that pre-defined parameters pertaining to the items of information are employed, rather than more general programming statements. For example, the particular attributes of a message which are to be utilized to define the prediction formula can be established ahead of time, and employed in the algorithms. For further information regarding this technique, reference is made to Goldberg, David E., Genetic Algorithms in Search, Optimization and Machine Learning, Addison-Wesley 1989.
In addition to content and correlation scores, other attributes can be employed. For example, event times can be used in the ranking equation, where older items might get lower scores. If a message is a call for submitting papers to a conference, its score might rise as the deadline approached, then fall when it had passed. These various types of data can be combined using any of the data analysis techniques described previously, as well as any other well-known analysis technique.
From the foregoing, it can be seen that the present invention provides a system for ranking information which is not based on only one factor, namely content. Rather, a determination is made on the basis of a combination of factors. In a preferred implementation, the present invention provides for social interaction within the community of users, since each individual can benefit from the experiences of others. A user who has written about a particular topic is more likely to have other messages relating to that same topic presented to him or her, without awareness of the authors of these other items of information.
The invention takes advantage of the fact that a community of users is participating in the presentation of information to users. In current systems, if a large number of readers each believe a message is significant, any given user is no more likely to see it than any other message. Conversely, the originator of a relatively uninteresting idea can easily broadcast it to a large number of people, even though they may have no desire to see it. In the system of the present invention, however, the relevance score of a particular message takes into account not only on the user's own interests, but also feedback from the community.
To facilitate an understanding of the invention, its principles have been explained with reference to specific embodiments thereof. It will be appreciated, however, that the practical applications of the invention are not limited to these particular embodiments. The scope of the invention is set forth in the following claims, rather than the foregoing description, and all equivalents which are consistent with the meaning of the claims are intended to be embraced therein.
Tiene, Kevin, Rose, Daniel E., Bornstein, Jeremy J., Ponceleón, Dulce B.
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