Title: Collaborative filtering for recommender systems: a scalability perspective

Authors: JoongHo Ahn, Taewha Hong

Addresses: Information Systems Area, College of Business Administration, Seoul National University, Seoul 151-742, Republic of Korea. ' Information Systems Area, College of Business Administration, Seoul National University, Seoul 151-742, Republic of Korea

Abstract: Recommender systems, now used in many websites, have a critical role in e-commerce systems. Among many techniques for recommender systems so far, collaborative filtering has proved to be one of the best solutions. However, there still remain some problems for collaborative filtering recommender systems, i.e. the scalability problem, which is the most critical one. In this paper, we focus on the scalability problem and present some algorithmic elements to improve the scalability of recommender systems. Then we show the trade-offs which the newly introduced elements bring about.

Keywords: collaborative filtering; recommender system; scalability; e-commerce; internet; world wide web.

DOI: 10.1504/IJEB.2004.004560

International Journal of Electronic Business, 2004 Vol.2 No.1, pp.77 - 92

Published online: 13 May 2004 *

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