Semantic user model inferences for travel recommender systems

Tourism Informatics: Visual Travel Recommender Systems, Social Communities, and User Interface Design

Volumn , Issue , 2009, Pages 22-37

  Yang, Yanwu ^a  

^a INSTITUTE OF GEOLOGY AND GEOPHYSICS   (China)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 84900136625     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.4018/978-1-60566-818-5.ch002     Document Type: Chapter

References (45)

1. Ardissono, L., Goy, A., Petrone, G., Segnan, M., & Torasso, P. (2001). Tailoring the recommendation of tourist information to heterogeneous user groups. In Proceedings of the Hypermedia: Openness, Structural Awareness, and Adaptivity, Int. Workshops OHS-7, SC-3 and AH-3 (LNCS 2266, pp. 280-295). Berlin, Germany: Springer Verlag.
2. Baader, F., Calvanese, D., McGuinness, D., Nardi, D., & Patel-Schneider, P. (2003). The description logic handbook: Theory, implementation and applications. Cambridge, UK: Cambridge University Press.
3. Baader, F., & Sattler, U. (2001). An overview of tableau algorithms for description logics. Studia Logica, 69, 5-40. doi:10.1023/A:1013882326814
4. Berka, T., & Plößnig, M. (2004). Designing recommender systems for tourism. In Proceedings of ENTER 2004, Kairo.
5. Calì, A., Calvanese, D., Colucci, S., Di Noia, T., & Donini, F. M. (2004). A logic-based approach for matching user profiles. In M. Gh. Negoita, R. J. Howlett, & L. C. Jain (Eds.), Proceedings of the Knowledge-Based Intelligent Information and Engineering Systems, 8th International Conference, KES 2004, Wellington, New Zealand (pp. 187-195).
6. Calvanese, D., De Giacomo, G., & Lenzerini, M. (1998). On the decidability of query containment under constraints. In Proceedings of the 17th ACM SIGACT SIGMOD SIGART Symposium on Principles of Database Systems (PODS'98) (pp. 149-158).
7. Carmagnola, F., Cena, F., Gena, C., & Torre, I. (2005). A multidimensional approach for the semantic representation of taxonomies and rules in adaptive hypermedia systems. In Proceedings of the PerSWeb'05 workshop (UM 2005).
8. Chiclana, F., Herrera, F., & Herrera-Viedma, E. (1998). Integrating three representation models in multipurpose decision making based on preference relations. Fuzzy Sets and Systems, 97, 33-48. doi:10.1016/S0165-0114(96)00339-9
9. Fink, J., & Kobsa, A. (2000). A review and analysis of commercial user modeling servers for personalization on the World Wide Web. User Modeling and User-Adapted Interaction, 10(3-4), 209-249.doi:10.1023/A:1026597308943
10. Friedman-Hill, E. (1995). Jess: The rule engine for the Java platform. Retrieved from http://herzberg.ca.sandia.gov/jess/
11. Haddawy, P., Ha, V., Restificar, A., Geisler, B., & Miyamoto, J. (2003). Preference elicitation via theory refinement. Journal of Machine Learning Research, 4, 317-337. doi:10.1162/153244304773633843
12. Hammond, K. (1989). Case-based planning: Viewing planning as a memory task. San Diego, CA: Academic Press.
13. Horrocks, I., Patel-Schneider, P. F., Boley, H., Tabet, S., Grosof, B., & Dean, M. (2004). SWRL: A Semantic Web rule language combining OWL and RuleML (W3C Member Submission, 21 May 2004). Retrieved from http://www.w3.org/Submission/2004/SUBM-SWRL-20040521/
14. Horrocks, I., Patel-Schneider, P. F., & van Harmelen, F. (2003). From SHIQ and RDF to OWL: The making of a Web ontology language. Journal of Web Semantics, 1(1), 7-26. doi:10.1016/j.web-sem.2003.07.001
15. Joachims, T. (2002). Optimizing search engines using clickthrough data. In Proceedings of the 8th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-02) (pp. 133-142). New York: ACM Press.
16. Kacprzyk, J. (1986). Group decision making with a fuzzy linguistic majority. Fuzzy Sets and Systems, 18, 105-118. doi:10.1016/0165-0114(86)90014-X
17. Keates, S., Laddon, P., Clarkson, P. J., & Robinson, P. (2002). User models and user physical capability. [UMUAI]Journal of User Modeling and User-Adapted Interaction, 12, 139-169.doi:10.1023/A:1015047002796
18. Kobsa, A. (2000). User modeling as a key factor in system personalization. Retrieved September 16, 2005, from http://www.zurich.ibm.com/~mrs/chi2000/contributions/kobsa.html
19. Kolodner, J. (1993). Case-based reasoning. San Mateo, CA: Morgan Kaufmann.
20. Linden, G., Hanks, S., & Lesh, N. (1997). Interactive assessment of user preference models: The automated travel assistant. In Proceedings of User Modeling.
21. Lutz, C. (2003). Description logics with concrete domains - a survey. In P.Balbiani, N.-Y. Suzuki, F. Wolter, and M. Zakharyaschev (Eds.), Advances in modal logics (Vol. 4). London: King's College Publications.
22. Milic-Frayling, N., Jones, R., Rodden, K., Smyth, G., Blackwell, A., & Sommerer, R. (2004). Smartback: Supporting users in back navigation. In Proceedings of the 13th conference on World Wide Web, New York, USA.
23. Noy, N. F., Fergerson, R. W., & Musen, M. A. (2000). The knowledge model of Protege-2000: Combining interoperability and flexibility. In Proceedings of the 2nd International Conference on Knowledge Engineering and Knowledge Management (EKAW'2000), Juan-les-Pins, France.
24. O'Connor, M. J., Knublauch, H., Tu, S. W., & Musen, M. A. (2005). Writing rules for the Semantic Web using SWRL and Jess. In Proceedings of the 8th International Protege Conference, Protege with Rules Workshop, Madrid, Spain.
25. Piaget, J., & Inhelder, B. (1969). The psychology of the child. New York: Basic Books.
26. RDF Core Working Group W3C Semantic Web Activity, W3C. (2004). Resource description framework (RDF) (W3C Recommendation, 10 February 2004). Retrieved from http://www.w3.org/TR/rdf-primer/
27. Riecken, D. (2000). Introduction: Personalized views of personalization. Communications of the ACM, 43(8), 27-28.
28. Riesbeck, C. K., & Schank, R. C. (1989). Inside case-based reasoning. Hillsdale, NJ: Lawrence Erlbaum.
29. Saaty, T. L. (1980). The analytic hierarchy process. New York: McGraw-Hill.
30. Sarwar, B., Karypis, G., Konstan, J., & Riedl, J. (2001). Item-based collaborative filtering recommendation algorithms. In Proceedings of the 10th International WWW Conference, Hong Kong.
31. Schafer, J. B., Konstan, J., & Riedl, J. (1999). Recommender systems in e-commerce. In Proceedings of the ACM Conference on Electronic Commerce (pp. 158-166).
32. Schild, K. (1991). A correspondence theory for terminological logics: Preliminary report. In Proceedings of IJCAI-91, 12th International Joint Conference on Artificial Intelligence, Sydney, Australia (pp. 466-471).
33. Shahabi, C., & Chen, Y. (2003). Web information personalization: Challenges and approaches. In Proceedings of the 3nd International Workshop on Databases in Networked Information Systems (DNIS 2003), Aizu-Wakamatsu, Japan (pp. 5-15).
34. Shavlik, J., & Towell, G. (1989). An approach to combining explanation-based and neural learning algorithms. Connection Science, 1(3), 233-255. doi:10.1080/09540098908915640
35. Shearin, S., & Lieberman, H. (2001). Intelligent profiling by example. In Proceedings of the International Conference on Intelligent User Interfaces (IUI 2001), Santa Fe, NM (pp. 145-152).
36. Sinner, A., Kleemann, T., & von Hessling, A. (2004). Semantic user profiles and their applications in a mobile environment. In Proceedings of the Artificial Intelligence in Mobile Systems 2004 (AIMS 2004).
37. Steel, N., Huppert, F. A., McWilliams, B., & Melzer, D. (2004). Physical and cognitive function. Retrieved from http://www.ifs.org.uk/elsa/report03/ch7.pdf
38. Sugiyama, K., Hatano, K., & Yoshikawa, M. (2004). Adaptive Web search based on user profile constructed without any effort from users. In Proceedings of the WWW 2004, New York, USA (pp. 675-684).
39. Towle, B., & Quinn, C. (2000). Knowledge-based recommender systems using explicit user models (Tech. Rep. WS-00-04, 74-77). Paper presented at the AAAI workshop.
40. Web Ontology Working Group W3C Semantic Web Activity, W3C. (2004). OWL Web ontology language (W3C Recommendation, 10 February 2004). Retrieved from http://www.w3.org/2001/sw/WebOnt/
41. Werthner, H., & Klein, S. (1999). Information technology and tourism - a challenging relationship. Berlin, Germany: Springer.
42. Worboys, M. F. (2001). Nearness relations in environmental space. International Journal of Geographical Information Science, 15(7), 633-651. doi:10.1080/13658810110061162
43. Yang, Y. (2006). Towards spatial Web personalization. Unpublished doctoral dissertation, Naval Academy Research Institute, France.
44. Yang, Y., & Claramunt, C. (2004). A flexible competitive neural network for eliciting user's preferences in Web urban spaces. In P. Fisher (Ed.), Developments in spatial data handling (pp. 41-57). Berlin, Germany: Springer-Verlag.
45. Yao, Y. (1995). Measuring retrieval effectiveness based on user preference of documents. Journal of the American Society for Information Science American Society for Information Science, 46(2), 133-145.doi:10.1002/(SICI)1097-4571(199503)46:2<133::AID-ASI6>3.0.CO;2-Z