Personalized trip information for e-tourism recommendation system based on bayes theorem

IFIP International Federation for Information Processing

Volumn 255, Issue , 2008, Pages 1271-1275

  Srisuwan, Patcharee ^a   Srivihok, Anongnart ^a  

^a KASETSART UNIVERSITY   (Thailand)

Author keywords

Bayes theorem; Business analytics; E Commerce; E tourism; Personalize; Recommendation system

Indexed keywords

BEHAVIORAL RESEARCH; ELECTRONIC COMMERCE; RECOMMENDER SYSTEMS; RESEARCH;

BAYES THEOREM; BUSINESS ANALYTICS; ETOURISM; PERSONALIZATION RECOMMENDATIONS; PERSONALIZE; PERSONALIZED RECOMMENDATION SYSTEMS; PRODUCTS AND SERVICES; USER BEHAVIORS;

INFORMATION SYSTEMS;

EID: 38049070376     PISSN: 15715736     EISSN: None     Source Type: Book Series    
DOI: 10.1007/978-0-387-76312-5_53     Document Type: Conference Paper

References (15)

1. S.H. Choi, S. Kang, and Y.J. Jeon, Personalized recommendation system based on product specification values. Expert Systems with Applications. Volume 31, Number 3, pp.607-616,(2004).
2. M. Balabanovic and Y. Shoham, Fab: Content-Based, Collaborative Recommendation, Communications of the ACM. Volume 40, pp.66-72, (1997).
3. M. Pazzani, J. Muramatsu, and D. Billsus, Syskill Webert: Identifying Interesting Web Sites, in Proc. of The National Conference on Artificial Intelligence (Portland, 1996), pp.54-61.
4. Q. Li and B.M. Kim, Clustering Approach for Hybrid Recommender System, in Proc. of The IEEE/WIC International conference on Web Intelligent (WI'03, 2003), pp.33-39.
5. D. Goldberg, D. Nichols, B.M. Oki, and D. Terry, Using Collaborative Filtering to Weave an Information Tapestry, Communications of the ACM Volume 35, Number 12, pp.61-70,(1992).
6. Y.Y. Shih and D.R. Liu, Hybrid recommendation approaches: Collaborative filtering via valuable content information, in Proc. of The 38th Hawaii International Conference on System Science, Track 8 (2005), pp.217-.
7. T. Joachims, D. Freitag, and T.M. Mitchell, Web Watcher: A tour guide for the World Wide Web, in Proc. of The International Joint Conference on Artificial Intelligence (1997),pp.770-775.
8. A. Srivihok and P. Sukonmanee, Intelligent Agent for e-Tourism: Personalization Travel, in Proc, of The 14th International World Wide Web Conference Workshop (WWW) (Chiba: Keio University, Japan, 2005), pp. 10-14.
9. W.P. Lee, C.H. Liu, and C.C. Lu, Intelligence agent-based systems for personalized recommendation in internet commerce. Expert Systems with Applications. Volume 22, Number 4, pp.275-284, (2002).
10. D. Godoy, S. Schiaffino, and A. Amandi, Interface agents personalizing Web-based tasks. Cognitive Systems Research. Volume 5, Number 3, pp.207-222, (2004).
11. P. Srisuwan and A. Srivihok, Using Bayesian Learning for Personalization Recommendation System for e - Tourism, in Proc. of The 4th International Joint Conference on Computer Science and Software Engineering (JCSSE) (Thailand, 2007), pp.515-521.
12. A.D. Martin and K.M. Quinn, Bayesian Learning about Ideal Points of U.S. Supreme Court Justices 1953-1999, Center for Statistics and the Social Sciences University of Washington (2001).
13. T-H. Lin, Bayesian Learning in Dual-Wing Harmoniums Applied to Information Retrieval and Genomics, International Journal of Computer Science & Applications Technomathematics Research Foundation. Volume 3, Number 3, pp. 12-26, (2006).
14. Y. Tsuruoka and T. Chikayama, Estimating Reliability of Contextual Evidences in Decision-List Classifiers under Bayesian Learning, in Proc. of The 6th NLPRS (2001), pp.701-707.
15. T.M. Mitchell, Machine Learning (McGraw-Hill: New York, 1997).