Capturing human intelligence in the net
Communications of the ACM
Web montage: a dynamic personalized start page
Proceedings of the 11th international conference on World Wide Web
Reinforcement Learning Architecture for Web Recommendations
ITCC '04 Proceedings of the International Conference on Information Technology: Coding and Computing (ITCC'04) Volume 2 - Volume 2
Integration of Relational Databases and Web Site Content for Product and Page Recommendation
IDEAS '04 Proceedings of the International Database Engineering and Applications Symposium
Hi-index | 0.00 |
In these days, they expect that computers comprehend characteristics of the user, for example interest and liking, to interact with computers. In this study, we constructed a system to construct an interest model of the user based on information in browsed Web pages by the user by extracting words and interword relationships. In this model, metadata is appended to words and interword relationships. Kinds of metadata of words are six, personal name, corporate name, site name, name of commodity, product name and location name. And metadata of interword relationships is prepared to clarify relationships of these words. This system makes a map by visualizing this model. And this system has functions to zoom and modify this map. We showed efficacy of this system by using evaluation experiment.