Abstract
Recommendations in e–commerce collaborative filtering are based on predicting the preference of a user for a given item according to historical records of other user’s preferences. This entails that the interpretation of user ratings are embodied in the prediction of preferences, so that such interpretation should be carefully studied. In this paper, the use of bipolar scales and aggregation procedures are experimentally compared to their unipolar counterparts, evaluating the adequacy of both techniques with regards to the human interpretation of rating scales. Results point out that bipolarity is closer to the human interpretation of opinions, which impacts the selection of recommended items.
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
Anderson, M., Ball, M., Boley, H., Greene, S., Howse, N., Lemire, D., McGrath, S.: RACOFI: A Rule-Applying Collaborative Filtering System. In: Proc. IEEE/WIC COLA 2003, Halifax, Canada (October 2003)
Grabisch, M., Lebreuche, C.: Bi–capacities for decision making on bipolar scales. In: Proceedings of EUROFUSE Workshop on Information Systems, pp. 185–190 (2002)
Herlocker, J., Konstan, J., Riedl, J.: Explaining Collaborative Filtering Recommendations. In: Proceedings of ACM 2000 Conference on Computer Supported Cooperative Work, pp. 241–250 (2000)
Izyumov, B., Kalinina, E., Wagenknecht, M.: Software tools for regression analysis of fuzzy data. In: Proceedings of 9th Zittau Fuzzy Colloquium, Zittau, Germany, pp. 221–229 (2001)
Konstan, J., Miller, B., Maltz, D., Herlocker, J., Gordon, L., Riedl, J.: GroupLens: Applying Collaborative Filtering to Usenet News. Communications of the ACM 40(3), 77–87 (1997)
Mesiarová, A., Lázaro, J., Calvo, T.: Bipolar Aggregation Operators. In: Proceedings of the International Summer School on Aggregation Operators and their Applications, pp. 119–122 (2003)
Paulson, P., Tzanavari, A.: Combining Collaborative and Content–Based Filtering Using Conceptual Graphs. In: Lawry, J., G. Shanahan, J., L. Ralescu, A. (eds.) Modelling with Words. LNCS, vol. 2873, pp. 168–185. Springer, Heidelberg (2003)
Resnick, P., Iacovou, N., Suchak, M., Bergstrom, P., Riedl, J.: GroupLens: An open architecture for collaborative filtering of netnews. In: Proceedings of ACM 1994 Conference on Computer Supported Cooperative Work, pp. 175–186. ACM, Chapel Hill (1994)
Sarwar, B.M., Karypis, G., Konstan, J.A., Riedl, J.: Analysis of Recommender Algorithms for E-Commerce. In: Proceedings of the ACM e–Commerce 2000 Conference, pp. 158–167 (2000)
Shardanand, U., Maes, P.: Social information filtering: Algorithms for automating “word of mouth”. In: Proceedings of CHI 1995 – Human Factors in Computing Systems, pp. 210–217 (1995)
Mehling, R.: A Simple Test for Measuring Intensity of Attitudes. Public Opinion Quarterly 23, 576–578 (1959)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2004 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Sicilia, MÁ., García, E. (2004). On the Use of Bipolar Scales in Preference–Based Recommender Systems. In: Bauknecht, K., Bichler, M., Pröll, B. (eds) E-Commerce and Web Technologies. EC-Web 2004. Lecture Notes in Computer Science, vol 3182. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30077-9_27
Download citation
DOI: https://doi.org/10.1007/978-3-540-30077-9_27
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22917-9
Online ISBN: 978-3-540-30077-9
eBook Packages: Springer Book Archive