Automatic, personalized online information and product services
First Claim
1. A computer-implemented method for providing automatic, personalized information services to a user u, the method comprising:
- a) transparently monitoring user interactions with data while the user is engaged in normal use of a computer;
b) updating user-specific data files, wherein the user-specific data files comprise the monitored user interactions with the data and a set of documents associated with the user;
c) estimating parameters of a learning machine, wherein the parameters define a User Model specific to the user and wherein the parameters are estimated in part from the user-specific data files;
d) analyzing a document d to identify properties of the document, the properties including (a) words of the document and (b) at least one additional property, the words of the document having (i) a first word frequency within the document and (ii) a second word frequency within other documents;
e) estimating a probability P(u|d) that an unseen document d is of interest to the user u, wherein the probability P(u|d) is estimated by applying the identified properties of the document to the learning machine having the parameters defined by the User Model; and
f) using the estimated probability to provide automatic, personalized information services to the user.
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Abstract
A method for providing automatic, personalized information services to a computer user includes the following steps: transparently monitoring user interactions with data during normal use of the computer; updating user-specific data files including a set of user-related documents; estimating parameters of a learning machine that define a User Model specific to the user, using the user-specific data files; analyzing a document to identify its properties; estimating the probability that the user is interested in the document by applying the document properties to the parameters of the User Model; and providing personalized services based on the estimated probability. Personalized services include personalized searches that return only documents of interest to the user, personalized crawling for maintaining an index of documents of interest to the user; personalized navigation that recommends interesting documents that are hyperlinked to documents currently being viewed; and personalized news, in which a third party server customized its interaction with the user.
45 Citations
19 Claims
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1. A computer-implemented method for providing automatic, personalized information services to a user u, the method comprising:
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a) transparently monitoring user interactions with data while the user is engaged in normal use of a computer; b) updating user-specific data files, wherein the user-specific data files comprise the monitored user interactions with the data and a set of documents associated with the user; c) estimating parameters of a learning machine, wherein the parameters define a User Model specific to the user and wherein the parameters are estimated in part from the user-specific data files; d) analyzing a document d to identify properties of the document, the properties including (a) words of the document and (b) at least one additional property, the words of the document having (i) a first word frequency within the document and (ii) a second word frequency within other documents; e) estimating a probability P(u|d) that an unseen document d is of interest to the user u, wherein the probability P(u|d) is estimated by applying the identified properties of the document to the learning machine having the parameters defined by the User Model; and f) using the estimated probability to provide automatic, personalized information services to the user. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18)
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19. A program storage device accessible by a central computer, tangibly embodying a program of instructions executable by the central computer to perform method steps for providing automatic, personalized information services to a user u, the method steps comprising:
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a) transparently monitoring user interactions with data while the user is engaged in normal use of a client computer in communication with the central computer; b) updating user-specific data files, wherein the user-specific data files comprise the monitored user interactions with the data and a set of documents associated with the user; c) estimating parameters of a learning machine, wherein the parameters define a User Model specific to the user and wherein the parameters are estimated in part from the user-specific data files; d) analyzing a document d to identify properties of the document, the properties including (a) words of the document and (b) at least one additional property, the words of the document having (i) a first word frequency within the document and (ii) a second word frequency within other documents; e) estimating a probability P(u|d) that an unseen document d is of interest to the user u, wherein the probability P(u|d) is estimated by applying the identified properties of the document to the learning machine having the parameters defined by the User Model; and f) using the estimated probability to provide automatic, personalized information services to the user.
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Specification