Method and system for extracting user behavior features to personalize recommendations
摘要:
A method for extracting user features based on user behaviors. The method uses webpage clickstream data of a current user to compute a path correlation between the current user and other users, selects a number of other users whose path correlation with the current user ranks among the highest, and then configures weights in connection to preset tags of websites visited by the selected other users, and computes a user correlation between the current user and the selected other users based on the preset tags and the weights. The method constructs weighted-directed graphs of webpage click paths based on click stream data, and converts computing user correlation to computing a similarity of weighted-directed graphs. The method further combines computing correlation of webpage tags to discover the user's clicking habits and personal preferences, and improve the accuracy and efficiency of user clustering.
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