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Recommender Systems Handbook pp 419–453Cite as

On the Evolution of Critiquing Recommenders

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Abstract

Over the past decade a significant amount of recommender systems research has demonstrated the benefits of conversational architectures that employ critique-based interfacing (e.g., Show me more like item A, but cheaper). The critiquing phenomenon has attracted great interest in line with the growing need for more sophisticated decision/recommendation support systems to assist online users who are overwhelmed by multiple product alternatives. Originally proposed as a powerful yet practical solution to the preference elicitation problem central to many conversational recommenders, critiquing has proved to be a popular topic in a variety of related areas (e.g., group recommendation, mixed-initiative recommendation, adaptive user interfacing, recommendation explanation). This chapter aims to provide a comprehensive, yet concise, source of reference for researchers and practitioners starting out in this area. Specifically, we present a deliberately non-technical overview of the critiquing research which has been covered in recent years.

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References

  1. Agrawal, R., Mannila, H., Srikant, R., Toivonen, H., Verkamo, A.I.: Fast discovery of association rules in large databases. Advances in Knowledge Discovery and Data Mining pp. 307–328 (1996)

    Google Scholar 

  2. Averjanova, O., Ricci, F., Nguyen, Q.N.: Map-based interaction with a conversational mobile recommender system. In: UBICOMM ’08: Proceedings of the 2008 The Second International Conference on Mobile Ubiquitous Computing, Systems, Services and Technologies, pp. 212– 218. IEEE Computer Society, Washington, DC, USA (2008)

    Google Scholar 

  3. Baatarjav, E.A., Phithakkitnukoon, S., Dantu, R.: Group recommendation system for facebook. In: OTM ’08: Proceedings of the OTM Confederated International Workshops and Posters on On the Move to Meaningful Internet Systems, pp. 211–219. Springer-Verlag, Berlin, Heidelberg (2008)

    Google Scholar 

  4. Burke, R.: The wasabi personal shopper: A case-based recommender system. In: Proceedings of the 11th National Conference on Innovative Applications of Artificial Intelligence, pp. 844–849. AAAI Press (1999). Menlo Park, CA, USA

    Google Scholar 

  5. Burke, R.: A case-based reasoning approach to collaborative filtering. In: E. Blanzieri, L. Portinale (eds.) Proceedings of the Fifth European Conference on Case-Based Reasoning, EWCBR ’00, pp. 370–379. Springer (2000). Trento, Italy

    Google Scholar 

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

    Article  MATH  Google Scholar 

  7. Burke, R., Hammond, K., Young, B.: Knowledge-based navigation of complex information spaces. In: Proceedings of the Thirteenth National Conference on Artificial Intelligence, pp. 462–468. AAAI Press/MIT Press (1996). Portland, OR

    Google Scholar 

  8. Burke, R.D., Hammond, K.J., Young, B.C.: The findme approach to assisted browsing. IEEE Expert: Intelligent Systems and Their Applications 12(4), 32–40 (1997)

    Google Scholar 

  9. Chen, L., Pu, P.: Evaluating critiquing-based recommender agents. In: In Proc. AAAI 2006, pp. 157–162 (2006)

    Google Scholar 

  10. Chen, L., Pu, P.: The evaluation of a hybrid critiquing system with preference-based recommendations organization. In: RecSys ’07: Proceedings of the 2007 ACM conference on Recommender systems, pp. 169–172. ACM, New York, NY, USA (2007)

    Google Scholar 

  11. Chen, L., Pu, P.: Hybrid critiquing-based recommender systems. In: IUI ’07: Proceedings of the 12th international conference on Intelligent user interfaces, pp. 22–31. ACM, New York, NY, USA (2007)

    Google Scholar 

  12. Chen, L., Pu, P.: Preference-Based Organization Interfaces: Aiding User Critiques in Recommender Systems, pp. 77–86. Springer-Verlag, Berlin, Heidelberg (2007)

    Google Scholar 

  13. Chen, L., Pu, P.: A cross-cultural user evaluation of product recommender interfaces. In: RecSys ’08: Proceedings of the 2008 ACM Conference on Recommender systems, pp. 75– 82. ACM, New York, NY, USA (2008)

    Google Scholar 

  14. Cohen S., Rokach L., Maimon O., Decision Tree Instance Space Decomposition with Grouped Gain-Ratio, Information Science, Volume 177, Issue 17, pp. 3592-3612 (2007)

    Google Scholar 

  15. Faltings, B., Pu, P., Torrens, M., Viappiani, P.: Designing example-critiquing interaction. In: IUI ’04: Proceedings of the 9th international conference on Intelligent user interfaces, pp. 22–29. ACM, New York, NY, USA (2004)

    Google Scholar 

  16. Faratin, P., Sierra, C., Jennnings, N.: Using similarity criteria to make issue trade-offs in automated negotiations. Artificial Intelligence 142(2), 205–237 (2002)

    Article  MathSciNet  Google Scholar 

  17. Ha, V., Haddawy, P.: Problem-focused incremental elicitation of multi-attribute utility models. In: Proceedings of the Thirteenth Conference on Uncertainty in Artificial Intelligence, (UAI-97), pp. 215–222. Morgan Kaufmann (1997). URL citeseer.ist.psu.edu/ ha97problemfocused.html. San Francisco

    Google Scholar 

  18. Hadzic, T., O’Sullivan, B.: Critique graphs for catalogue navigation. In: RecSys ’08: Proceedings of the 2008 ACM conference on Recommender systems, pp. 115–122. ACM, New York, NY, USA (2008)

    Google Scholar 

  19. Hammond, K., Burke, R., Schmitt, K.: A case-based approach to knowledge navigation. In: D. Leake (ed.) Case-Based Reasoning Experiences, Lessons and Future Directions., pp. 125– 136. AAAI Press (1996)

    Google Scholar 

  20. Jameson, A.: More than the sum of its members: Challenges for group recommender systems. In: AVI ’04: Proceedings of the working conference on Advanced visual interfaces, pp. 48– 54. ACM, New York, NY, USA (2004)

    Google Scholar 

  21. Lee, K., Joshi, K., McIvor, R.: Understanding multicultural differences in online satisfaction. In: SIGMIS-CPR ’07: Proceedings of the 2007 ACM SIGMIS CPR conference on Computer personnel research, pp. 209–212. ACM, New York, NY, USA (2007)

    Google Scholar 

  22. Linden, G., Hanks, S., Lesh, N.: Interactive assessment of user preference models: The automated travel assistant. In: C.P.A. Jameson, C. Tasso (eds.) User Modeling: Proceedings of the Sixth International Conference, pp. 67–78. Springer Wien (1997)

    Google Scholar 

  23. Lodge, C.: The impact of culture on usability: Designing usable products for the international user. In: N.M. Aykin (ed.) Usability and Internationalization. HCI and Culture, Second International Conference on Usability and Internationalization, UI-HCII 2007, Held as Part of HCI International 2007, Beijing, China, July 22-27, 2007, Proceedings, Part I, pp. 365–368. Springer (2007)

    Google Scholar 

  24. Masthoff, J., Gatt, A.: In pursuit of satisfaction and the prevention of embarrassment: Affective state in group recommender systems. User Modeling and User-Adapted Interaction 16(3-4), 281–319 (2006)

    Article  Google Scholar 

  25. McCarthy, J., Anagnost, T.: Musicfx: An arbiter of group preferences for computer aupported collaborative workouts. In: Proc. of Conference on Computer Supported Cooperative Work, pp. 363–372 (1998)

    Google Scholar 

  26. McCarthy, K., Reilly, J., McGinty, L., Smyth, B.: On the dynamic generation of compound critiques in conversational recommender systems. In: Adaptive Hypermedia and Adaptive Web-Based Systems, Third International Conference, AH 2004, Eindhoven, The Netherlands, August 23-26, 2004, Proceedings, Lecture Notes in Computer Science, vol. 3137, pp. 176– 184. Springer (2004)

    Google Scholar 

  27. McCarthy, K., Reilly, J., McGinty, L., Smyth, B.: Experiments in dynamic critiquing. In: IUI ’05: Proceedings of the 10th international conference on Intelligent user interfaces, pp. 175–182. ACM, New York, NY, USA (2005)

    Google Scholar 

  28. McCarthy, K., Reilly, J., Smyth, B., McGinty, L.: Generating diverse compound critiques. Artif. Intell. Rev. 24(3-4), 339–357 (2005)

    Article  Google Scholar 

  29. McCarthy, K., Salam´o, M., Coyle, L., McGinty, L., Smyth, B., Nixon, P.: Cats: A synchronous approach to collaborative group recommendation. In: G. Sutcliffe, R. Goebel (eds.) Proceedings of the Nineteenth International Florida Artificial Intelligence Research Society Conference, Melbourne Beach, Florida, USA, May 11-13, 2006, pp. 86–91. AAAI Press (2006)

    Google Scholar 

  30. McCarthy, K., Salam´o, M., Coyle, L., McGinty, L., Smyth, B., Nixon, P.: Group recommender systems: A critiquing based approach. In: IUI ’06: Proceedings of the 11th international conference on Intelligent user interfaces, pp. 267–269. ACM, New York, NY, USA (2006)

    Google Scholar 

  31. McCarthy, K., Salam´o, M., McGinty, L., Smyth, B.: The needs of the many: A case-based group recommender system. In: ICCBR ’06: Proceedings of the 11th international conference on Intelligent user interfaces, pp. 196–210. Springer LNCS (2006)

    Google Scholar 

  32. McGinty, L., Smyth, B.: The role of diversity in conversational systems. In: D. Bridge, K. Ashley (eds.) Proceedings of the Fifth International Conference on Case-Based Reasoning (ICCBR-03). Springer (2003). Troindheim, Norway.

    Google Scholar 

  33. McGinty, L., Smyth, B.: Tweaking critiquing. In: Proceedings of the Workshop on Personalization and Web Techniques at the International Joint Conference on Artificial Intelligence (IJCAI-03). Morgan-Kaufmann (2003). Acapulco, Mexico

    Google Scholar 

  34. McGinty, L., Smyth, B.: Adaptive selection: An analysis of critiquing and preference-based feedback in conversational recommender systems. Int. J. Electron. Commerce 11(2), 35–57 (2006)

    Article  Google Scholar 

  35. McSherry, D.: Similarity and compromise. In: K. Ashley, D. Bridge (eds.) Case-Based Reasoning Research and Development. LNAI Vol.2689, pp. 291–305. Springer (2003)

    Google Scholar 

  36. McSherry, D.: Explaining the pros and cons of conclusions in cbr. In: P. Funk, P.A. González- Calero (eds.) Advances in Case-Based Reasoning, 7th European Conference, ECCBR 2004, Madrid, Spain, August 30 - September 2, 2004, Proceedings, pp. 317–330. Springer (2004)

    Google Scholar 

  37. McSherry, D.: Retrieval failure and recovery in recommender systems. Artif. Intell. Rev. 24(3-4), 319–338 (2005)

    Article  Google Scholar 

  38. McSherry, D., Aha, D.: Mixed-initiative relaxation of constraints in critiquing dialogues. In: ICCBR ’07: Proceedings of the 7th international conference on Case-Based Reasoning, pp. 107–121. Springer-Verlag, Berlin, Heidelberg (2007)

    Google Scholar 

  39. McSherry, D., Aha, D.W.: Avoiding long and fruitless dialogues in critiquing. In: M. Bramer, F. Coenen, A. Tuson (eds.) Research and Development in Intelligent Systems XXIII. BCS Conference Series, pp. 173–186. Springer, London (2006)

    Google Scholar 

  40. McSherry, D., Aha, D.W.: The ins and outs of critiquing. In: M.M. Veloso (ed.) Proceedings of the 20th International Joint Conference on Artificial Intelligence (IJCAI), Hyderabad, India, January 6-12, 2007, pp. 962–967 (2007)

    Google Scholar 

  41. Nguyen, Q., Ricci, F.: User preferences initialization and integration in critique-based mobile recommender systems. In: In Proc. 5th Int’l Workshop Artificial Intelligence in Mobile Systems (AIMS 04),, p. pp. 7178 (2004)

    Google Scholar 

  42. Nguyen, Q., Ricci, F., Cavada, D.: Critique-based recommendations for mobile users: Gui design and evaluation. In: In Proceedings of the 3rd InternationalWorkshop on HCI in Mobile Guides, in conjunction with the 6th International Conference on Mobile Human-Computer Interaction (2004). Glasgow, Scotland.

    Google Scholar 

  43. Nguyen, Q.N., Ricci, F.: Replaying live-user interactions in the off-line evaluation of critiquebased mobile recommendations. In: RecSys ’07: Proceedings of the 2007 ACM conference on Recommender systems, pp. 81–88. ACM, New York, NY, USA (2007)

    Google Scholar 

  44. Nguyen, Q.N., Ricci, F.: Long-term and session-specific user preferences in a mobile recommender system. In: IUI ’08: Proceedings of the 13th international conference on Intelligent user interfaces, pp. 381–384. ACM, New York, NY, USA (2008)

    Google Scholar 

  45. Noiwan, J., Norcio, A.F.: Cultural differences on attention and perceived usability: Investigating color combinations of animated graphics. Int. J. Hum.-Comput. Stud. 64(2), 103–122 (2006)

    Google Scholar 

  46. O’Connor, M., Cosley, D., Konstan, J., Riedl, J.: Polylens: A recommender system for groups of users. In: Proc. of European Conference on Computer-Supported Cooperative Work, pp. 199–218 (2001)

    Google Scholar 

  47. Park, Y.J., Chang, K.N.: Individual and group behavior-based customer profile model for personalized product recommendation. Expert Syst. Appl. 36(2), 1932–1939 (2009)

    Article  MathSciNet  Google Scholar 

  48. Payne, J., Bettman, J., Johnson, E.: The Adaptive Decision Maker. Cambridge University Press (1993)

    Google Scholar 

  49. Plua, C., Jameson, A.: Collaborative preference elicitation in a group travel recommender system. In: Proceedings of the AH 2002 Workshop on Recommendation and Personalization in eCommerce, pp. 148–154. Malaga, Spain (2002)

    Google Scholar 

  50. Prada, R., Paiva, A.: Believable groups of synthetic characters. In: Proceedings of the 4th International Joint Conference on Autonomous Agents and Multi-Agent Systems, pp. 37–43. The Netherlands (2005)

    Google Scholar 

  51. Pu, P., Chen, L.: Trust building with explanation interfaces. In: IUI ’06: Proceedings of the 11th international conference on Intelligent user interfaces, pp. 93–100. ACM, New York, NY, USA (2006)

    Google Scholar 

  52. Pu, P., Chen, L.: Trust-inspiring explanation interfaces for recommender systems. Know.- Based Syst. 20(6), 542–556 (2007)

    Article  Google Scholar 

  53. Pu, P., Faltings, B.: Personalized navigation of heterogeneous product spaces using smartclient. In: IUI ’02: Proceedings of the 7th international conference on Intelligent user interfaces, pp. 212–213. ACM, New York, NY, USA (2002)

    Google Scholar 

  54. Pu, P., Faltings, B.: Decision tradeoff using example-critiquing and constraint programming. Constraints 9(4), 289–310 (2004)

    Article  Google Scholar 

  55. Pu, P., Z., H., Kumar, P.: Evaluating example-based search tools. In: EC ’04: Proceedings of the 5th ACM conference on Electronic commerce, pp. 208–217. ACM, New York, NY, USA (2004)

    Google Scholar 

  56. Reilly, J., McCarthy, K., McGinty, L., Smyth, B.: Dynamic critiquing. In: P. Funk, P.A. González-Calero (eds.) Advances in Case-Based Reasoning, 7th European Conference, ECCBR 2004, Madrid, Spain, August 30 - September 2, 2004, Proceedings, Lecture Notes in Computer Science, vol. 3155, pp. 763–777. Springer (2004)

    Google Scholar 

  57. Reilly, J., McCarthy, K., McGinty, L., Smyth, B.: Explaining compound critiques. Artif. Intell. Rev. 24(2), 199–220 (2005)

    Article  Google Scholar 

  58. Reilly, J., McCarthy, K., McGinty, L., Smyth, B.: Incremental critiquing. Knowl.-Based Syst. 18(4-5), 143–151 (2005)

    Article  Google Scholar 

  59. Reilly, J., Smyth, B., McGinty, L., McCarthy, K.: Critiquing with confidence. In: H. Muñoz- Avila, F. Ricci (eds.) Case-Based Reasoning, Research and Development, 6th International Conference, on Case-Based Reasoning, ICCBR 2005, Chicago, IL, USA, August 23-26, 2005, Proceedings, Lecture Notes in Computer Science, vol. 3620, pp. 436–450. Springer (2005)

    Google Scholar 

  60. Reilly, J., Zhang, J., McGinty, L., Pu, P., Smyth, B.: A comparison of two compound critiquing systems. In: IUI ’07: Proceedings of the 12th international conference on Intelligent user interfaces, pp. 317–320. ACM, New York, NY, USA (2007)

    Google Scholar 

  61. Ricci, F., Nguyen, Q.N.: Critique-based mobile recommender systems,. GAI Journal, GAI Press Volume 24, Number 4 (2004)

    Google Scholar 

  62. Ricci, F., Nguyen, Q.N.: Acquiring and revising preferences in a critique-based mobile recommender system. IEEE Intelligent Systems 22(3), 22–29 (2007)

    Article  Google Scholar 

  63. Salamo, M., Reilly, J., McGinty, L., Smyth, B.: Improving incremental critiquing. In: In Procedings of the 16th Conference on Artificial Intelligence and Cognitive Science (AICS05), pp. 379–388 (2005)

    Google Scholar 

  64. Shearin, S., Lieberman, H.: Intelligent profiling by example. In: IUI ’01: Proceedings of the 6th international conference on Intelligent user interfaces, pp. 145–151. ACM, New York, NY, USA (2001)

    Google Scholar 

  65. Smyth, B., McGinty, L.: Improving the Performance of Recommender Systems that Use Critiquing, chap. Intelligent Techniques for Web Personalization, pp. 114–132. 978-3-540- 29846-5. Springer (2005)

    Google Scholar 

  66. Sørmo, F., Cassens, J., Aamodt, A.: Explanation in case-based reasoning-perspectives and goals. Artificial Intelligence Review 24(2), 109–143 (2005)

    Article  Google Scholar 

  67. Spiekermann, S., Paraschiv, C.: Motivating Human-Agent Interaction: Transferring Insights from Behavioral Marketing to Agent Design, pp. 255–285. Kluwer Academic Publishers (2002)

    Google Scholar 

  68. Viappiani, P., Faltings, B., Pu, P.: Preference-based search using example-critiquing with suggestions. Journal of Artificial Intelligence Research 27, 2006 (2006)

    Google Scholar 

  69. Weld, D., Anderson, C., Domingos, P., Etzioni, O., Lau, T., Gajos, K.,Wolfman, S.: Automatically personalizing user interfaces. In: Proceedings of the 18th International Joint Confer13 On the Evolution of Critiquing Recommenders 453 ence Artificial Intelligence (IJCAI-03), pp. 1613–1619. Morgan Kaufman (2003). Acapulco, Mexico

    Google Scholar 

  70. Williams, M.: What makes rabbit run? International Journal of Man-Machine Studies 21, 333–352 (1984)

    Article  Google Scholar 

  71. Williams, M., Tou, F.: Rabbit: An interface for database access. In: In Proceedings of the ACM’82 Conference, pp. 83–87. ACM, New York, USA (1982)

    Google Scholar 

  72. Zhang, J., Jones, N., Pu, P.: A visual interface for critiquing-based recommender systems. In: EC ’08: Proceedings of the 9th ACM conference on Electronic commerce, pp. 230–239. ACM, New York, NY, USA (2008)

    Google Scholar 

  73. Zhang, J., Pu, P.: A comparative study of compound critique generation in conversational recommender systems. In: V.P. Wade, H. Ashman, B. Smyth (eds.) Adaptive Hypermedia and Adaptive Web-Based Systems, 4th International Conference, AH 2006, Dublin, Ireland, June 21-23, 2006, Proceedings, Lecture Notes in Computer Science, vol. 4018, pp. 234–243. Springer (2006)

    Google Scholar 

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Authors and Affiliations

  1. UCD School of Computer Science and Informatics, University College Dublin, Dublin 4, Ireland

    Lorraine McGinty

  2. Google Inc., 5 Cambridge Center, Cambridge, MA, 02142, US

    James Reilly

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  1. Lorraine McGinty
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Correspondence to Lorraine McGinty .

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Editors and Affiliations

  1. , Faculty of Computer Science, Free University of Bozen-Bolzano, Piazza Domenicani 3, Bolzano, 39100, Italy

    Francesco Ricci

  2. , Dept. Information Systems Engineering, Ben-Gurion University of the Negev, Beer-Sheva, 84105, Israel

    Lior Rokach

  3. Dept. Information Systems Engineering, Ben-Gurion University of the Negev, Beer-Sheva, Israel

    Bracha Shapira

  4. School of Communication,, Information & Library Studies, Rutgers University, Huntington Street 4, New Brunswick, 08901-1071, New Jersey, USA

    Paul B. Kantor

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McGinty, L., Reilly, J. (2011). On the Evolution of Critiquing Recommenders. In: Ricci, F., Rokach, L., Shapira, B., Kantor, P. (eds) Recommender Systems Handbook. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-85820-3_13

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