Language Models for Collaborative Filtering Neighbourhoods

  • Daniel Valcarce
  • Javier Parapar
  • Álvaro Barreiro
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9626)

Abstract

Language Models are state-of-the-art methods in Information Retrieval. Their sound statistical foundation and high effectiveness in several retrieval tasks are key to their current success. In this paper, we explore how to apply these models to deal with the task of computing user or item neighbourhoods in a collaborative filtering scenario. Our experiments showed that this approach is superior to other neighbourhood strategies and also very efficient. Our proposal, in conjunction with a simple neighbourhood-based recommender, showed a great performance compared to state-of-the-art methods (NNCosNgbr and PureSVD) while its computational complexity is low.

Keywords

Recommender systems Language models Collaborative filtering Neighbourhood 

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Daniel Valcarce
    • 1
  • Javier Parapar
    • 1
  • Álvaro Barreiro
    • 1
  1. 1.Information Retrieval Lab, Computer Science DepartmentUniversity of A CoruñaA CoruñaSpain

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