Improving the performance of unit critiquing

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 7379 LNCS, Issue , 2012, Pages 176-187

  Mandl, Monika ^a   Felfernig, Alexander ^a  

^a GRAZ UNIVERSITY OF TECHNOLOGY   (Austria)

Author keywords

Conversational Recommendation; Critiquing Systems; Recommender Systems

Indexed keywords

CONVERSATIONAL INTERACTION; CONVERSATIONAL RECOMMENDATIONS; CONVERSATIONAL RECOMMENDER SYSTEMS; CRITIQUING SYSTEMS; EMPIRICAL STUDIES; FEEDBACK STRATEGIES; LOW COSTS; NEAREST NEIGHBORS; RECOMMENDATION EFFICIENCY;

MATHEMATICAL MODELS; RECOMMENDER SYSTEMS;

ALGORITHMS;

EID: 84863619651     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-31454-4_15     Document Type: Conference Paper

References (17)

1. McCarthy, K., McGinty, L., Smyth, B.: Dynamic Critiquing: An Analysis of Cognitive Load. In: Proceedings of the 16th Irish Conference on Artificial Intelligence and Cognitive Science, pp. 19-28 (2005)
2. Reilly, J., Zhang, J., McGinty, L., Pu, P., Smyth, B.: Evaluating compound critiquing recommenders: a real-user study. In: Proceedings of the 8th ACM Conference on Electronic Commerce, pp. 114-123 (2007)
3. Reilly, J., McCarthy, K., McGinty, L., Smyth, B.: Incremental Critiquing. In: Research and Development in Intelligent Systems XXI, pp. 101-114 (2005)
4. Burke, R.D., Hammond, K.J., Young, B.C.: The FindMe Approach to Assisted Browsing. IEEE Expert, 32-40 (1997)
5. McCarthy, K., Reilly, J., McGinty, L., Smyth, B.: On the Dynamic Generation of Compound Critiques in Conversational Recommender Systems. In: De Bra, P.M.E., Nejdl, W. (eds.) AH 2004. LNCS, vol. 3137, pp. 176-184. Springer, Heidelberg (2004)
6. Zhang, J., Pu, P.: A Comparative Study of Compound Critique Generation in Conversational Recommender Systems. In: Wade, V.P., Ashman, H., Smyth, B. (eds.) AH 2006. LNCS, vol. 4018, pp. 234-243. Springer, Heidelberg (2006) (Pubitemid 44077612)
7. McCarthy, K., Salem, Y., Smyth, B.: Experience-Based Critiquing: Reusing Critiquing Experiences to Improve Conversational Recommendation. In: Bichindaritz, I., Montani, S. (eds.) ICCBR 2010. LNCS, vol. 6176, pp. 480-494. Springer, Heidelberg (2010)
8. Rokach, L.: Taxonomy for characterizing ensemble methods in classification tasks: A review and annotated bibliography. Computational Statistics & Data Analysis (2009) (in press, corrected proof)
9. Bell, R.M., Koren, Y., Volinsky, C.: The BellKor solution to the Netflix Prize (2007)
10. Piotte, M., Chabbert, M.: The Pragmatic Theory Solution to the Netflix Grand Prize. Netflix Prize Documentation (2009)
11. Töscher, A., Jahrer, M.: The BigChaos Solution to the Netflix Prize 2008 (2008)
12. Burke, R.D., Hammond, K.J., Young, B.C.: Knowledge-Based Navigation of Complex Information Spaces. In: AAAI/IAAI, vol. 1, pp. 462-468 (1996)
13. Salamó, M., Smyth, B., McCarthy, K., Reilly, J., McGinty, L.: Reducing critiquing repetition in conversational recommendation. In: Proceedings of the IJCAI 2005 Workshop on Multi-Agent Information Retrieval and Recommender Systems, pp. 55-61 (2005)
14. Smyth, B., McGinty, L.: An Analysis of Feedback Strategies in Conversational Recommender Systems. In: Proceedings of the Fourteenth National Confer1ence on Artificial Intelligence and Cognitive Science (AICS 2003), pp. 211-216 (2003)
15. Burke, R.D.: Interactive Critiquing for Catalog Navigation in E-Commerce. Artificial Intelligence Review 18, 245-267 (2002)
16. Keeney, R.L., Raiffa, H.: Decisions with Multiple Objectives: Preferences and Value Tradeoffs. John Wiley & Sons, New York (1976)
17. Chen, L., Pu, P.: Critiquing-based recommenders: survey and emerging trends. In: User Modeling and User-Adapted Interaction, pp. 1-26 (2011)