Abstract
Critiquing-based recommender systems offer users a conversational paradigm to provide their feedback, named critiques, during the process of viewing the current recommendation. In this way, the system is able to learn and adapt to the users’ preferences more precisely so that better recommendation could be returned in the subsequent iteration. Moreover, recent works on experience-based critiquing have suggested the power of improving the recommendation efficiency by making use of relevant sessions from other users’ histories so as to save the active user’s interaction effort. In this paper, we present a novel approach to processing the history data and apply it to the compound critiquing system. Specifically, we develop a history-aware collaborative compound critiquing method based on preference-based compound critique generation and graph-based similar session identification. Through experiments on two data sets, we validate the outperforming efficiency of our proposed method in comparison to the other experience-based methods. In addition, we verify that incorporating user histories into compound critiquing system can be significantly more effective than the corresponding unit critiquing system.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Adomavicius, G., Tuzhilin, A.: Toward the next generation of recommender systems: A survey of the state-of-the-art and possible extensions. IEEE Transactions on Knowledge and Data Engineering 17(6), 734–749 (2005)
Becerra, C., Gonzalez, F., Gelbukh, A.: Visualizable and explicable recommendations obtained from price estimation functions. In: Proc. ACM RecSys 2011, pp. 27–34 (2011)
Burke, R.D., Hammond, K.J., Yound, B.: The findme approach to assisted browsing. IEEE Expert 12(4), 32–40 (1997)
Chen, L.: User Decision Improvement and Trust Building in Product Recommender Systems. PhD thesis, Ecole Polytechnique Federale De Lausanne (EPFL), Lausanne, Switzerland (August 2008)
Chen, L., Pu, P.: Preference-based organization interfaces: Aiding user critiques in recommender systems. In: Conati, C., McCoy, K., Paliouras, G. (eds.) UM 2007. LNCS (LNAI), vol. 4511, pp. 77–86. Springer, Heidelberg (2007)
Chen, L., Pu, P.: Critiquing-based recommenders: survey and emerging trends. User Modeling and User-Adapted Interaction 22(1-2), 125–150 (2012)
Keeney, R.L.: Decisions with Multiple Objectives: Preferences and Value Trade-offs. Cambridge University Press (1993)
Linden, G., Hanks, S., Lesh, N.: Interactive assessment of user preference models: The automated travel assistant. In: Proc. UM 1997, pp. 67–68 (1997)
Mandl, M., Felfernig, A.: Improving the performance of unit critiquing. In: Masthoff, J., Mobasher, B., Desmarais, M.C., Nkambou, R. (eds.) UMAP 2012. LNCS, vol. 7379, pp. 176–187. Springer, Heidelberg (2012)
McCarthy, K., McGinty, L., Smyth, B.: Dynamic critiquing: An analysis of cognitive load. In: Proc. ICAICS 2005, pp. 19–28 (2005)
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)
Mccarthy, K., Reilly, J., Smyth, B., Mcginty, L.: Generating diverse compound critiques. Artificial Intelligence Review 24(3-4), 339–357 (2005)
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)
Quinlan, J.R.: Combining instance-based and model-based learning. In: Proc. ICML 1993, pp. 236–243 (1993)
Reilly, J., McCarthy, K., McGinty, L., Smyth, B.: Dynamic critiquing. In: Funk, P., González Calero, P.A. (eds.) ECCBR 2004. LNCS (LNAI), vol. 3155, pp. 763–777. Springer, Heidelberg (2004)
Reilly, J., McCarthy, K., McGinty, L., Smyth, B.: Incremental critiquing. Knowledge-Based Systems 18(4), 143–151 (2005)
Salem, Y., Hong, J.: History-aware critiquing-based conversational recommendation. In: Proc. WWW 2013, pp. 63–64 (2013)
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)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Xie, H., Chen, L., Wang, F. (2014). Collaborative Compound Critiquing. In: Dimitrova, V., Kuflik, T., Chin, D., Ricci, F., Dolog, P., Houben, GJ. (eds) User Modeling, Adaptation, and Personalization. UMAP 2014. Lecture Notes in Computer Science, vol 8538. Springer, Cham. https://doi.org/10.1007/978-3-319-08786-3_22
Download citation
DOI: https://doi.org/10.1007/978-3-319-08786-3_22
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-08785-6
Online ISBN: 978-3-319-08786-3
eBook Packages: Computer ScienceComputer Science (R0)