Approach to modeling user interests using conceptual clustering

The exponential increase of internet resources accelerated the development of effective personalization techniques. A new method for modeling user interest, named UIM²C² (user interest modeling method based on conceptual clustering) was presented. The method analyzed documents that each user ever browsed and created a suffix tree. According to different pair-wise base cluster similarity thresholds, base clusters could be merged in the range of different granularity. Combining with the inclusion relation between merged base clusters under different granularity, an interest hierarchy was generated. UIM²C² carried out incremental, unsupervised concept learning over Web documents so that user profiles could be acquired and updated easily. Experimental results prove the effectiveness of the method in Web page recommendation.