Browse > Article
http://dx.doi.org/10.5391/JKIIS.2007.17.6.754

Learning for User Profile Based on Negative Feedback and Reinforcement Learning  

Son, Ki-Jun (경북대학교 컴퓨터공학과)
Lim, Soo-Yeon (경북대학교 컴퓨터공학과)
Lee, Sang-Jo (경북대학교 컴퓨터공학과)
Publication Information
Journal of the Korean Institute of Intelligent Systems / v.17, no.6, 2007 , pp. 754-759 More about this Journal
Abstract
The information recommendation system offers selected documents according to information needs of dynamic users. User's needs are expressed as profiles consisting of one or more words and may be changed into some specifics through relevance feedback made by users during the recommendation process. In previous research, users have entered relevance information by taking part in explicit relevance feedbacks and learned user profiles using the positive relevance feedbacks. In this paper, we learn user profiles using not only positive relevance feedback but negative relevance feedback and reinforcement learning. To compare the proposed with previous method, we performed experiments to evaluate recommendation performance of the same topic. As a result, the former shows the improved performance than the latter does.
Keywords
Profile Learning; Relevance Feedback; Negative Feedback; Recommender System;
Citations & Related Records
연도 인용수 순위
  • Reference
1 Seo, Y, Zang, B., 'Personalized Web Document Filtering Using Reinforcement Learning,' Applied Artificial Intelligence, Vol. 15(7), pp. 665-685, 2001   DOI   ScienceOn
2 M. Balabanovic, Y. Shoham, 'Learning Information Retrieval Agent: Experiments with Automated Web Browsing,' In Proceeding of the AAAI Spring Symposium on Information Gathering, Stanford, CA, March 1995
3 R. S. Sutton, A. G. Barto, Reinforcement Learning: An Introduction, MIT Press, 1998
4 L. P. Kaelbling, M. L. L. Littman and A. W. Moore, 'Reinforcement Learning: A Survey,' Journal of AI Research, vol. 4, pp. 237-285, 1996
5 강승식, 'HAM v.470c: 한국어 형태소 분석기와 한국어 분석 모듈,' http://nlp.kookmin.ac.kr/ham/ham.html
6 M. Pazzani, J. Muramatsu, D. Billsus 'Syskill & Webert: Identifying interesting web sites,' National Conference on Artificial Intelligence, vol. 1, pp. 54-61, 1996
7 T. M. Mitchell, Machine Learning, McGraw Hill, 1997
8 Shardanand. U., and Maes 'Social Information Filtering: Algorithmic for Automating Word of Mouth,' In Conference on Human Factors In Computing System(CHI'95), pp. 210-217, 1995
9 Tak W. Yan, Hector Garcia-Molina, 'SIFT-A Tool for Wide-Area Information Dissemination,' Proceeding of the 1995 USENEX Techical Conference, pp. 177-186, 1995
10 G. Salton, M. J. McGill, Introduction to modern information retrieval, McGraw Hill, 1983