Reducing development and maintenance efforts for web-based recommender applications

International Journal of Web Engineering and Technology

Volumn 3, Issue 3, 2007, Pages 329-351

  Felfernig, Alexander ^a  

^a UNIVERSITY OF KLAGENFURT   (Austria)

Author keywords

Experimental evaluation; Improving knowledge acquisition processes; Testing and debugging recommender knowledge bases; Web based recommenders

Indexed keywords

COMPUTER GRAPHICS; CUSTOMER SATISFACTION; KNOWLEDGE ACQUISITION; LARGE SCALE SYSTEMS; ONLINE SYSTEMS; SALES;

DEBUGGING RECOMMENDER KNOWLEDGE BASES; EXPERIMENTAL EVALUATION; IMPROVING KNOWLEDGE ACQUISITION PROCESSES; WEB-BASED RECOMMENDERS;

WEB SERVICES;

EID: 34250744238     PISSN: 14761289     EISSN: 17419212     Source Type: Journal    
DOI: 10.1504/IJWET.2007.012060     Document Type: Article

References (30)

1. Ardissono, L., Felfernig, A., Friedrich, G., Jannach, D., Petrone, G., Schäfer, R. and Zanker, M. (2003) 'A framework for the development of personalized, distributed web-based configuration systems', AI Magazine, Vol. 24, No. 3, pp.93-108.
2. Burke, R. (2000) 'Knowledge-based recommender systems', Encyclopedia of Library and Information Systems, Vol. 69, No. 32.
3. Burke, R. (2002) 'Hybrid recommender systems: survey and experiments', User Modeling and User-Adapted Interaction, Vol. 12, No. 4, pp.331-370.
4. Edvardson, J. (1999) 'A survey on automatic test data generation', 2nd Conference on Computer Science and Engineering CCSSe99, Linköping, Sweden, pp.21-28.
5. Felfernig, A. (2005) 'Koba4MS: selling complex products and services using knowledge-based recommender technologies', in G. Müller and K. Lin (Eds.) 7th IEEE International Conference on E-Commerce Technology (CEC'05), Munich, Germany, pp.92-100.
6. Felfernig, A., Friedrich, G., Jannach, D. and Stumptner, M. (2004) 'Consistency-based diagnosis of configuration knowledge bases', AI Journal, Vol. 2, No. 152, pp.213-234.
7. Felfernig, A., Friedrich, G., Jannach, D., Stumptner, M. and Zanker, M. (2003) 'Configuration knowledge representations for semantic web applications', AI Engineering Design, Analysis and Manufacturing Journal, Vol. 17, pp.31-50.
8. Felfernig, A., Isak, K. and Kruggel, T. (2006) 'Knowledge-based recommendation: technologies and experiences from projects', 17th European Conference on Artificial Intelligence (ECAI'06), Riva del Garda, Italy, p. to appear.
9. Felfernig, A. and Kiener, A. (2005) 'Knowledge-based interactive selling of financial services using FSAdvisor', 17th Innovative Applications of Artificial Intelligence Conference (IAAI'05), Pittsburgh, Pennsylvania, pp.1475-1482.
10. Felfernig, A. and Shchekotykhin, K. (2006) 'Debugging user interface descriptions of knowledge-based recommender applications', ACM International Conference on Intelligent User Interfaces, Sydney, Australia, pp.234-241.
11. Godfrey, P. (1997) 'Minimization in cooperative response to failing database queries', International Journal of Cooperative Information Systems, Vol. 6, No. 2, pp.95-149.
12. Herlocker, J.L., Konstan, J.A., Terveen, L.G. and Riedl, J. (2004) 'Evaluating collaborative filtering recommender systems', ACM Trans. on Inf. Systems, Vol. 22, No. 1, pp.5-53.
13. Jiang, B., Wang, W. and Benbasat, I. (2005) 'Multimedia-based interactive advising technology for online consumer decision support', Comm. of the ACM, Vol. 48, No. 9, pp.93-98.
14. Jorgensen, P. (2002) Software Testing, A Craftsman's Approach, CRC Press.
15. Junker, U. (2004) 'QUICKXPLAIN: preferred explanations and relaxations for over-constrained problems', 19th National Conf. on AI (AAAI04), pp.167-172.
16. M. Tallis, J. and Kim, Y.G. (1999) 'User studies of knowledge acquisition tools: methodology and lessons learned', KAW-99.
17. McSherry, D. (2004) 'Maximally successful relaxations of unsuccessful queries', 15th Conference on Artificial Intelligence and Cognitive Science, pp. 127-136.
18. Mittal, S. and Frayman, F. (1989) 'Towards a generic model of configuration tasks', 11th International Joint Conference on AI, Detroit, MI, pp.1395-1401.
19. Montaner, M., Lopez, B. and La Rose, J.D. (2003) 'A taxonomy of recommender agents on the internet', Artificial Intelligence Review, Vol. 19, pp.285-330.
20. Pazzani, M. and Billsus, D. (1997) 'Learning and revising user profiles: the identification of interesting web sites', Machine Learning, Vol. 27, pp.313-331.
21. Preece, A., Talbot, S. and Vignollet, L. (1997) 'Evaluation of verification tools for knowledge-based systems', International Journal of Human-Computer Studies, Vol. 47, No. 3, pp.629-658.
22. Reiter, R. (1987) 'A theory of diagnosis from first principles', AI Journal, Vol. 23, No. 1, pp.57-95.
23. Resnick, P., Iacovou, N., Suchak, M., Bergstrom, P. and Riedl, J. (1994) 'GroupLens: an open architecture for collaborative filtering of Netnews', ACM Conf. on Computer Supported Coop. Work, pp. 175-186.
24. Sarwar, B., Karypis, G., Konstan, J.A. and Riedl, J. (2001) 'Item-based collaborative filtering recommendation algorithms', 10th Intl. WWW Conference, pp.285-295.
25. Schafer, J., Konstan, J. and Riedl, J. (2000) 'Electronic commerce recommender applications', Journal of Data Mining and Knowledge Discovery, Vol. 5, Nos. 1-2, pp.115-152.
26. Shih, Y-Y. and Liu, D-R. (2005) 'Hybrid recommendation approaches: collaborative filtering via valuable content information', 38th Hawaii Intl. Conf. on System Sciences (HICSS'05), p.217b.
27. Terveen, L. and Hill, W. (2001) 'Beyond recommender systems: helping people help each other', HCI in the New Millennium, Addison Wesley.
28. Thompson, C., Göker, M. and Langley, P. (2004) 'A personalized system for conversational recommendations', Journal of Artificial Intelligence Research, Vol. 21, pp.393-428.
29. Tiihonen, J., Soininen, T., Niemelä, I. and Sulonen, R. (2002) 'Empirical testing of a weight constraint rule based configurator', ECAI 2002 Workshop on Configuration, Lyon, France, pp. 17-22.
30. Tsang, E. (1993) Foundations of Constraint Satisfaction, London: Academic Press.