Using contextual information and multidimensional approach for recommendation

Expert Systems with Applications

Volumn 36, Issue 2 PART 1, 2009, Pages 1268-1279

  Weng, Sung Shun ^a   Lin, Binshan ^b   Chen, Wen Tien ^a  

^a FU JEN CATHOLIC UNIVERSITY   (Taiwan)

^b LOUISIANA STATE UNIVERSITY   (United States)

Author keywords

Collaborative filtering; Contextual information; Multidimensional recommendation; Recommendation system

Indexed keywords

COLLABORATIVE FILTERING; DATA WAREHOUSES; ELECTRONIC COMMERCE; SALES;

COLLABORATIVE FILTERING RECOMMENDATIONS; CONTENT-BASED RECOMMENDATION; CONTEXTUAL INFORMATION; MULTI-DIMENSIONAL ANALYSIS; MULTI-DIMENSIONAL APPROACH; MULTIDIMENSIONAL RECOMMENDATION; ON-LINE ANALYTICAL PROCESSING; PERSONALIZED RECOMMENDATION;

RECOMMENDER SYSTEMS;

EID: 56349120805     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2007.11.056     Document Type: Article

References (30)

1. Adomavicius, G., & Tuzhilin, A. (2001). Extending recommendation system s: A multidimensional approach. In Proceedings of the international joint conference on artificial intelligence (IJCAI-01), Workshop on intelligent techniques for web personalization. Seattle.
2. Adomavicius G., Sankaranarayanan R., Sen S., and Tuzhilin A. Incorporating contextual information in recommendation system s using a multidimensional approach. ACM Transactions on Information Systems 23 1 (2005) 103-145
3. Adomavicius G., and Tuzhilin A. Using data mining methods to build customer profiles. IEEE Computer 34 2 (2001) 74-82
4. Adomavicius G., and Tuzhilin A. Toward the next generation of recommendation system s: A survey of the state-of-the-art and possible extensions. IEEE Transactions on Knowledge and Data Engineering 17 6 (2005) 734-749
5. Billsus, D., & Pazzani, M. J. (1998). Learning collaborative information filters. In Proceedings of the 15th international conference on machine learning (pp. 46-54). Madison.
6. Burke R. Knowledge-based recommendation systems. In: Kent A. (Ed). Encyclopedia of Library and Information Systems 69 32 (2000) 1-23
7. Burke R. Hybrid recommendation system s: survey and experiments. User Modeling and User-Adapted Interaction 12 4 (2002) 331-370
8. Cao Y., and Li Y. An intelligent fuzzy-based recommendation system for consumer electronic products. Expert Systems with Applications 33 1 (2007) 230-240
9. Chaudhuri S., and Dayal U. An overview of data warehousing and OLAP technology. ACM SIGMOD Record 26 1 (1997) 65-74
10. Deshpande M., and Karypis G. Item-based top-N recommendation algorithms. ACM Transactions on Information Systems 22 1 (2004) 143-177
11. Herlocker J.L., and Konstan J.A. Content-independent task-focused recommendation. IEEE Internet Computing 5 6 (2001) 40-47
12. Herlocker J.L., Konstan J.A., Terveen L.G., and Riedl J.T. Evaluating collaborative filtering recommendation system s. ACM Transactions on Information Systems 22 1 (2004) 5-53
13. Hou J.L., and Yang S.T. A critical customer identification model for technology and service providers. International Journal of Services and Standards 2 4 (2007) 417-436
14. Jung, S., Harris, K., Webster, J., & Herlocker, J. L. (2004). SERF: Integrating human recommendations with search. In Proceedings of the 13th conference on information and knowledge management (pp. 571-580).
15. Kazienko P., and Kiewra M. Personalized recommendation of web pages, chapter 10. In: Nguyen T. (Ed). Intelligent technologies for inconsistent knowledge processing (2004), Advanced Knowledge International, Adelaide, SouthAustralia 163-183
16. Lawrence R.D., Almasi G.S., Kotlyar V., Viveros M.S., and Duri S. Personalization of supermarket product recommendations. Data Mining and Knowledge Discovery 5 1/2 (2001) 11-32
17. Lee H.Y., Ahn H., and Han I. VCR: Virtual community recommender using the technology acceptance model and the user's needs type. Expert Systems with Applications 33 4 (2007) 984-995
18. Lee H.J., and Park S.J. MONERS: A news recommender for the mobile web. Expert Systems with Applications 32 1 (2007) 143-150
19. Linden G., Smith B., and York J. Amazon.com recommendations item to item collaborative filtering. IEEE Internet Computing 7 1 (2003) 76-80
20. Maguire S., Koh S.C.L., and Huang C. Identifying the range of customer listening tools: A logical pre-cursor to CRM?. Industrial Management & Data Systems 107 4 (2007) 567-586
21. Mobasher B., Dai H., Luo T., and Nakagawa M. Discovery and evaluation of aggregate usage profiles for web personalization. Data Mining and Knowledge Discovery 6 1 (2002) 61-82
22. Pazzani M. A framework for collaborative, content-based and demographic filtering. Artificial Intelligence Review 13 5-6 (1999) 393-408
23. Rezguil Y. Knowledge systems and value creation: An action research investigation. Industrial Management & Data Systems 107 2 (2007) 166-182
24. Schafer, J. B., Konstan, J. A., & Riedl, J. (1999). Recommendation systems in e-commerce. In Proceedings of the first ACM conference on electronic commerce (pp. 158-166). Denver.
25. Shih, Y. Y., & Liu, D. R. (2005). Hybrid recommendation approaches: Collaborative filtering via valuable content information. In Proceedings of 38th Hawaii international conference on system sciences. Big Island.
26. Smith A.D. Collaborative commerce through web-based information integration technologies. International Journal of Innovation and Learning 4 3 (2007) 127-144
27. Tiraweerakhajohn, C., & Pinngern, O. (2004). Finding item neighbors in item-based collaborative filtering by adding item content. In Proceedings of the 8th international conference on control, automation, robotics and vision (pp. 1674-1678). Kunming.
28. Weng S.S., and Liu M.J. Feature-based recommendations for one-to-one marketing. Expert Systems with Applications 26 4 (2004) 493-508
29. Yang, W., Wang, Z., & You, M. (2004). An improved collaborative filtering method for recommendations generation. In Proceedings of the 2004 IEEE international conference on systems, man and cybernetics (pp. 4135-4139). The Hague.
30. Yong S.K., Yum B.J., Song J., and Su M.K. Development of a recommendation system based on navigational and behavioral patterns of customers in e-commerce sites. Expert Systems with Applications 28 (2005) 381-393