Article

Product recommendation with interactive query management and twofold similarity

Authors:

Francesco Ricci,

Adriano Venturini,

Nader Mirzadeh,

Marisa NonesAuthors Info & Claims

ICCBR'03: Proceedings of the 5th international conference on Case-based reasoning: Research and Development

Pages 479 - 493

Published: 23 June 2003 Publication History

Abstract

This paper describes an approach to product recommendation that combines in a novel way content- and collaborative-based filtering techniques. The system helps the user to specify a query that filters out unwanted products in electronic catalogues (content-based). Moreover, if the query produces too many or no results, the system suggests useful query changes that save the gist of the original request. This process goes on iteratively till a reasonable number of products is selected. Then, the selected products are ranked exploiting a case base of recommendation sessions (collaborative-based). Among the user selected items the system ranks higher items that are similar to those selected by other users in similar sessions (twofold similarity). The approach has been applied to a web travel application and it has been evaluated with real users. The proposed approach: a) reduces dramatically the number of user queries, b) reduces the number of browsed products and c) the selected items are found first on the ranked list.

References

[1]

B. Arslan and F. Ricci. Case based session modeling and personalization in a travel advisory system. In F. Ricci and B. Smyth, editors, Proceedings of the AH'20002 Workshop on Recommendation and Personalization in eCommerce, pages 60-69, Malaga, Spain, May, 28th 2002.

[2]

J. Breese, D. Heckerman, and C. Kadie. Empirical analysis of predictive algorithms for collaborative filtering. In Proceedings of the Fourteenth Conference on Uncertainty in Artificial Intelligence, Madison, WI, July 1998. Morgan Kaufmann Publisher.

Digital Library

[3]

D. Bridge and A. Ferguson. Diverse product recommendations using an expressive language for case retrieval. In S. Craw and A. Preece, editors, Advances in Case-Based Reasoning, Proceedings of the 6th European Conference on Case Based Reasoning, ECCBR 2002, pages 43-57, Aberdeen, Scotland, 4-7 September 2002. Springer Verlag.

Digital Library

[4]

R. Burke. Knowledge-based recommender systems. In J. E. Daily, A. Kent, and H. Lancour, editors, Encyclopedia of Library and Information Science, volume 69. Marcel Dekker, 2000.

[5]

R. Burke. Hybrid recommender systems: Survey and experiments. User Modeling and User-Adapted Interaction, 12(4):331-370, 2002.

Digital Library

[6]

P. Cunningham, R. Bergmann, S. Schmitt, R. Traphöner, S. Breen, and B. Smyth. Websell: Intelligent sales assistants for the world wide web. In R. Weber and C. Wangenheim, editors, Procs. of the Workshop Programme at the Fourth International Conference on Case-Based Reasoning, 2001.

[7]

D. R. Fesenmaier, F. Ricci, E. Schaumlechner, K. Wöber, and C. Zanella. DIETORECS: Travel advisory for multiple decision styles. In A. J. Frew, M. Hitz, and P. O'Connors, editors, Information and Communication Technologies in Tourism 2003, pages 232-241. Springer, 2003.

[8]

M. H. Göker and C. A. Thomson. Personalized conversational case-based recommendation. In Advances in case-based reasoning: 5th European workshop, EWCBR- 2000, Trento, Italy, September 6-9, 2000: proceedings, pages 99-111. Springer, 2000.

Digital Library

[9]

K. M. Gupta, D. W. Aha, and N. Sandhu. Exploiting taxonomic and causal relations in conversational case retrieval. In S. Craw and A. Preece, editors, Advances in Case-Based Reasoning, Proceedings of the 6th European Conference on Case Based Reasoning, ECCBR 2002, pages 133-147, Aberdeen, Scotland, 4-7 September 2002. Springer Verlag.

Digital Library

[10]

F. Ricci, B. Arslan, N. Mirzadeh, and A. Venturini. ITR: a case-based travel advisory system. In S. Craw and A. Preece, editors, 6th European Conference on Case Based Reasoning, ECCBR 2002, pages 613-627, Aberdeen, Scotland, 4-7 September 2002. Springer Verlag.

Digital Library

[11]

F. Ricci, N. Mirzadeh, and A. Venturini. Intelligent query managment in a mediator architecture. In 2002 First International IEEE Symposium "Intelligent Systems', pages 221-226, Varna, Bulgaria, September 10-12 2002.

[12]

J. B. Schafer, J. A. Konstan, and J. Riedl. E-commerce recommendation applications. Data Mining and Knowledge Discovery, 5(1/2):115-153, 2001.

Digital Library

[13]

S. Schmitt, P. Dopichaj, and P. Domínguez-Marín. Entropy-based vs. similarity-influenced: attribute selection methods for dialogs tested on different electronic commerce domains. In S. Craw and A. Preece, editors, Advances in Case-Based Reasoning, Proceedings of the 6th European Conference on Case Based Reasoning, ECCBR 2002, pages 380-394, Aberdeen, Scotland, 4-7 September 2002. Springer Verlag.

Digital Library

[14]

H. Shimazu. ExpertClerk: Navigating shoppers buying process with the combination of asking and proposing. In B. Nebel, editor, Proceedings of the Seventeenth International Joint Conference on Artificial Intelligence, IJCAI 2001, pages 1443- 1448, Seattle, Washington, USA, August 4-10 2001. Morgan Kaufmann.

Digital Library

[15]

D. O. Sullivan, D. Wilson, and B. Smyth. Improving case-based recommendation, a collaborative filtering approach. In S. Craw and A. Preece, editors, Advances in Case-Based Reasoning, Proceedings of the 6th European Conference on Case Based Reasoning, ECCBR 2002, pages 278-291, Aberdeen, Scotland, 4-7 September 2002. Springer Verlag.

Digital Library

[16]

D. R. Wilson and T. R. Martinez. Improved heterogeneous distance functions. Journal of Artificial Intelligence Research, 11:1-34, 1997.

Digital Library

Cited By

Jannach DLudewig MLerche L(2017)Session-based item recommendation in e-commerceUser Modeling and User-Adapted Interaction10.1007/s11257-017-9194-127:3-5(351-392)Online publication date: 1-Dec-2017
https://dl.acm.org/doi/10.1007/s11257-017-9194-1
Schnabel TBennett PDumais SJoachims TBourdeau JHendler JNkambou RHorrocks IZhao B(2016)Using Shortlists to Support Decision Making and Improve Recommender System PerformanceProceedings of the 25th International Conference on World Wide Web10.1145/2872427.2883012(987-997)Online publication date: 11-Apr-2016
https://dl.acm.org/doi/10.1145/2872427.2883012
Jannach DLerche LJugovac MWerthner HZanker MGolbeck JSemeraro G(2015)Adaptation and Evaluation of Recommendations for Short-term Shopping GoalsProceedings of the 9th ACM Conference on Recommender Systems10.1145/2792838.2800176(211-218)Online publication date: 16-Sep-2015
https://dl.acm.org/doi/10.1145/2792838.2800176
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Information & Contributors

Information

Published In

cover image Guide Proceedings

ICCBR'03: Proceedings of the 5th international conference on Case-based reasoning: Research and Development

June 2003

734 pages

ISBN:3540404333

Editors:
Kevin D. Ashley
University of Pittsburgh, Learning Research and Development Center, Pittsburgh, PA
,
Derek G. Bridge
University College Cork, Department of Computer Science, Cork, Ireland

Sponsors

Kaidara Software
NTNU: Norwegian University of Science and Technology

Publisher

Springer-Verlag

Berlin, Heidelberg

Publication History

Published: 23 June 2003

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Cited By

Jannach DLudewig MLerche L(2017)Session-based item recommendation in e-commerceUser Modeling and User-Adapted Interaction10.1007/s11257-017-9194-127:3-5(351-392)Online publication date: 1-Dec-2017
https://dl.acm.org/doi/10.1007/s11257-017-9194-1
Schnabel TBennett PDumais SJoachims TBourdeau JHendler JNkambou RHorrocks IZhao B(2016)Using Shortlists to Support Decision Making and Improve Recommender System PerformanceProceedings of the 25th International Conference on World Wide Web10.1145/2872427.2883012(987-997)Online publication date: 11-Apr-2016
https://dl.acm.org/doi/10.1145/2872427.2883012
Jannach DLerche LJugovac MWerthner HZanker MGolbeck JSemeraro G(2015)Adaptation and Evaluation of Recommendations for Short-term Shopping GoalsProceedings of the 9th ACM Conference on Recommender Systems10.1145/2792838.2800176(211-218)Online publication date: 16-Sep-2015
https://dl.acm.org/doi/10.1145/2792838.2800176
Vinagre JJorge AGama J(2015)An overview on the exploitation of time in collaborative filteringWiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery10.1002/widm.11605:5(195-215)Online publication date: 1-Sep-2015
https://dl.acm.org/doi/10.1002/widm.1160
Kabassi K(2010)ReviewTelematics and Informatics10.1016/j.tele.2009.05.00327:1(51-66)Online publication date: 1-Feb-2010
https://dl.acm.org/doi/10.1016/j.tele.2009.05.003
Gurski FWanke E(2009)The NLC-width and clique-width for powers of graphs of bounded tree-widthDiscrete Applied Mathematics10.1016/j.dam.2008.08.031157:4(583-595)Online publication date: 20-Feb-2009
https://dl.acm.org/doi/10.1016/j.dam.2008.08.031
Zanker MJessenitschnig M(2009)Case-studies on exploiting explicit customer requirements in recommender systemsUser Modeling and User-Adapted Interaction10.1007/s11257-008-9048-y19:1-2(133-166)Online publication date: 1-Feb-2009
https://dl.acm.org/doi/10.1007/s11257-008-9048-y
Felfernig AFriedrich GIsak KShchekotykhin KTeppan EJannach D(2009)Automated debugging of recommender user interface descriptionsApplied Intelligence10.1007/s10489-007-0105-831:1(1-14)Online publication date: 1-Aug-2009
https://dl.acm.org/doi/10.1007/s10489-007-0105-8
Jannach DKreutler G(2007)Rapid development of knowledge-based conversational recommender applications with advisor suiteJournal of Web Engineering10.5555/2011243.20112496:2(165-192)Online publication date: 1-Jun-2007
https://dl.acm.org/doi/10.5555/2011243.2011249
Smyth B(2007)Case-based recommendationThe adaptive web10.5555/1768197.1768210(342-376)Online publication date: 1-Jan-2007
https://dl.acm.org/doi/10.5555/1768197.1768210
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