DYNAMIC PREDICTION OF ONLINE SHOPPER'S INTENT USING A COMBINATION OF PREDICTION MODELS
First Claim
Patent Images
1. A computer implemented method for user intent analysis, comprising:
- providing a processor configured for receiving a Web server request from a user through at least one of a plurality of channels;
said processor collecting data traffic of the user at the Web server;
said processor analyzing the collected data traffic of the user to determine a Web path taken by the user at the Web site during a visiting session as said Web site;
said processor beginning to infer user intent from the Web path as the visiting session commences;
said processor classifying the user based on said inferred user intent before the user leaves the Web site;
said processor training an assistance model using the user intent that was inferred; and
said processor providing virtual assistance by proactively including search suggestions to the user based on the assistance model.
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Accused Products
Abstract
Online browsing behavior is used to predict the intent of online users dynamically. The category of online user is predicted and the prediction can be used to provide assistance to the user, if required. Such prediction is based on a combination of a Naïve'"'"'s Bayes classifier and a Markov model.
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Citations
25 Claims
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1. A computer implemented method for user intent analysis, comprising:
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providing a processor configured for receiving a Web server request from a user through at least one of a plurality of channels; said processor collecting data traffic of the user at the Web server; said processor analyzing the collected data traffic of the user to determine a Web path taken by the user at the Web site during a visiting session as said Web site; said processor beginning to infer user intent from the Web path as the visiting session commences; said processor classifying the user based on said inferred user intent before the user leaves the Web site; said processor training an assistance model using the user intent that was inferred; and said processor providing virtual assistance by proactively including search suggestions to the user based on the assistance model.
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2. A computer implemented method for user intent analysis, comprising:
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providing a processor configured for receiving a Web server request from a user through at least one of a plurality of channels; said processor collecting data traffic of the user at the Web server; said processor analyzing Web path taken by the user in real time while the user is visiting a Web site; and based upon said path analysis, said processor using dynamic models to infer user intent from the Web path as the user visit to the Web site commences. - View Dependent Claims (3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13)
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14. An apparatus for user intent analysis, comprising:
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a processor executing instructions to implement a user classifier module, said user classifier module classifying users into one of a plurality of categories by taking into account browsing and cognitive behavior of said user, said user classifier module generating a response variable that captures the user'"'"'s intent; said user classifier module transforming navigational data of said user into a new data set; said processor implementing a user tracker module, said user tracker module tracking and monitoring user browsing behavior in real time from any of a plurality of sources and reporting user activities to said user classifier module; said processor implementing a page categorizer module, said page categorizer module reducing Web site URL'"'"'s of pages visited by said user during an online session into a smaller group of categories; said processor modeling captured user-related data concerning the user'"'"'s visits to a Web site and transforming said data; said processor dynamically predicting the user'"'"'s intent once the data is modeled; and said processor using resulting data to create training and testing data for a plurality of users. - View Dependent Claims (15, 16, 17)
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18. A computer implemented method for user intent analysis, comprising:
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providing a processor executing instructions for preprocessing raw data; said processor obtaining transformed data; said processor measuring a set of predictors for an online user who is visiting a Web site, wherein the set of predictors is available at the outset of the user visit; said processor considering a variable length set of variables comprising a sequence of uniform resource locators (URLs) that are viewed by said user during said visit up to a particular click; said processor developing a model to predict the intent of the user by computing probabilities at said particular click and basing a decision on a comparison with a pre-determined threshold; as the user'"'"'s journey of navigating the Web site progresses, said processor updating and evolving an understanding of the user'"'"'s intent; and said processor engaging the user by offering to the user a suitable form of interaction in response to the user'"'"'s queries. - View Dependent Claims (19, 20, 21)
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22. An apparatus for user intent analysis, comprising:
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a processor receiving a Web server request from a user through at least one of a plurality of channels; said processor collecting data traffic of the user at the Web server; said processor analyzing the collected data traffic of the user to determine a Web path taken by the user at the Web site during a visiting session as said Web site; said processor beginning to infer user intent from the Web path as the visiting session commences; said processor classifying the user based on inferred the user intent before the user leaves the Web site; said processor training an assistance model using the user intent that was inferred; and said processor providing virtual assistance proactively including search suggestions to the user based on the assistance model.
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23. An apparatus for user intent analysis, comprising:
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a processor receiving a Web server request from a user through at least one of a plurality of channels; said processor collecting data traffic of the user at the Web server; said processor analyzing Web path taken by the user in real time while the user is visiting a Web site; and based upon said path analysis, said processor using dynamic models to infer user intent from the Web path as the user visit to the Web site commences.
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24. An apparatus for user intent analysis, comprising:
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a processor categorizing intent of one or more users in real time while they are searching one or more online commerce sites, wherein each user connects to a Web site with an intention of performing one more specific tasks; said processer inferring said user'"'"'s intent early in a browsing session by tracking a Web path that the user follows on the Web site; said processer using one or more dynamic models to predict user intent before the user abandons the Web site, based on a combination of models comprising a Naï
ve Bayes Classifier and a Markov model; andsaid processer adapting said combined models depending on the user'"'"'s location along a search path; wherein as the user progresses farther along the Web path, the model'"'"'s prediction of the user'"'"'s intent becomes more accurate.
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25. A computer implemented method for user intent analysis, comprising:
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providing a processor executing instructions for categorizing intent of one or more users in real time while they are searching one or more online commerce sites, wherein each user connects to a Web site with an intention of performing one more specific tasks; said processer inferring said user'"'"'s intent early in a browsing session by tracking a Web path that the user follows on the Web site; said processer using one or more dynamic models to predict user intent before the user abandons the Web site, based on a combination of models comprising a Naï
ve Bayes Classifier and a Markov model; andsaid processer adapting said combined models depending on the user'"'"'s location along a search path; wherein as the user progresses farther along the Web path, the model'"'"'s prediction of the user'"'"'s intent becomes more accurate.
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Specification