A unified approach of factor models and neighbor based methods for large recommender systems

Gábor Takács, István Pilászy, Bottyán Németh, Domonkos Tikk

Research output: Chapter in Book/Report/Conference proceedingConference contribution

10 Citations (Scopus)

Abstract

Matrix factorization (MF) based approaches have proven to be efficient for rating-based recommendation systems. In this paper, we propose a hybrid approach that alloys an improved MF and the so-called NSVD1 approach, resulting in a very accurate factor model. After that, we propose a unification of factor models and neighbor based approaches, which further improves the performance. The approaches are evaluated on the Netflix Prize dataset, and they provide very low RMSE, and favorable running time. Our best solution presented here with Quiz RMSE 0.8851 outperforms all published single methods in the literature.

Original languageEnglish
Title of host publication1st International Conference on the Applications of Digital Information and Web Technologies, ICADIWT 2008
Pages186-191
Number of pages6
DOIs
Publication statusPublished - Dec 30 2008
Event1st International Conference on the Applications of Digital Information and Web Technologies, ICADIWT 2008 - Ostrava, Czech Republic
Duration: Aug 4 2008Aug 6 2008

Publication series

Name1st International Conference on the Applications of Digital Information and Web Technologies, ICADIWT 2008

Other

Other1st International Conference on the Applications of Digital Information and Web Technologies, ICADIWT 2008
CountryCzech Republic
CityOstrava
Period8/4/088/6/08

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ASJC Scopus subject areas

  • Computer Science Applications
  • Information Systems
  • Software

Cite this

Takács, G., Pilászy, I., Németh, B., & Tikk, D. (2008). A unified approach of factor models and neighbor based methods for large recommender systems. In 1st International Conference on the Applications of Digital Information and Web Technologies, ICADIWT 2008 (pp. 186-191). [4664342] (1st International Conference on the Applications of Digital Information and Web Technologies, ICADIWT 2008). https://doi.org/10.1109/ICADIWT.2008.4664342