Int. J. Business Intelligence and Data Mining, Vol. 1, No. 1, 2005 107 Copyright © 2005 Inderscience Enterprises Ltd. A hybrid framework for similarity-based recommendations Nikos Karacapilidis* and Lefteris Hatzieleftheriou Industrial Management and Information Systems Lab, MEAD, University of Patras, 26500 Rio Patras, Greece Fax: +30 2610 997260 E-mail: nikos@mech.upatras.gr E-mail: lxatzis@yahoo.com *Corresponding author Abstract: By exploiting the concept of fuzzy similarity measures, this paper presents a hybrid recommendation framework that builds on the strengths of knowledge-based and collaborative filtering techniques. Following a multi-criteria approach, the proposed framework is able to provide users with a ranked list of alternatives, while it also permits them to submit their evaluations on the existing items of the database. Much attention is given to the extent to which the user evaluation may affect the values of the stored items. The applicability of our approach is demonstrated through an already implemented web-based tool, namely CityGuide, which provides recommendations about visiting different cities of a country. Issues related to the robustness of our framework and the selection of the appropriate similarity measure are also discussed. Keywords: recommendation techniques; recommender systems; web services; similarity measures. Reference to this paper should be made as follows: Karacapilidis, N. and Hatzieleftheriou, L. (2005) ‘A hybrid framework for similarity-based recommendations’, Int. J. Business Intelligence and Data Mining, Vol. 1, No. 1, pp.107–121. Biographical notes: Nikos Karacapilidis holds an Associate Professor position at the Industrial Management and Information Systems Lab, MEAD, University of Patras, Greece. His current research interests are on the areas of intelligent information systems, decision making, knowledge management, and semantic web. More information can be found at http:// www.mech.upatras.gr/~nikos/ Lefteris Hatzieleftheriou holds a Diploma in Mechanical Engineering (MEAD, University of Patras, Greece). His research interests focus on the area of web services. 1 Introduction Basically due to the overwhelming volume of information available online and the growing attractiveness of applications deployed on the internet, the development of recommender systems has been receiving increasing interest in the last few years. Such