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Article Abstract

Title: Collaborative filtering for recommender systems: a scalability perspective
  Author: JoongHo Ahn, Taewha Hong   Email author(s)
  Address: 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
  Journal: International Journal of Electronic Business 2004 - Vol. 2, No.1  pp. 77 - 92
  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
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