DYNAMIC PREDICTION OF ONLINE SHOPPER'S INTENT USING A COMBINATION OF PREDICTION MODELS

摘要

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.

主权项

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.