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Evaluating Recommender System Using Multiagent-Based Simulator

Case Study of Collaborative Filtering Simulation
  • Ryosuke Saga
  • Kouki Okamoto
  • Hiroshi Tsuji
  • Kazunori Matsumoto
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 156)

Abstract

This paper describes a agent-based simulation system to evaluate recommender systems. Recommender systems have attracted attention to present items found by preference of users. Many algorithms for recommender system are developed but the comparisons between their algorithms are difficult because of limited data set and the difficulty of constructing simulator environment. In order to resolve them, we develop agent-based recommender system simulator. This simulator constructs the simulator environment based on the network model, and lets recommender agent recommend items to agents, evaluates the items, and summarizes(outputs) the recommendation results. In the experiment on 100 agents, we can confirm the usability of our simulator because of recapturing the feature of collaborative filtering by this simulator.

Keywords

Recommender System Collaborative Filter Computer Support Cooperative Work Simulator User Recommendation Result 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag GmbH Berlin Heidelberg 2013

Authors and Affiliations

  • Ryosuke Saga
    • 1
  • Kouki Okamoto
    • 2
  • Hiroshi Tsuji
    • 1
  • Kazunori Matsumoto
    • 2
  1. 1.Osaka Prefecture UniversitySakaiJapan
  2. 2.Kanagawa Institute of TechnologyAtsugiJapan

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