Using error-correcting dependencies for collaborative filtering

  • Authors:
  • Galina Bogdanova;Tsvetanka Georgieva

  • Affiliations:
  • Institute of Mathematics and Informatics, Bulgarian Academy of Sciences, P.O. Box 323, Veliko Tarnovo, Bulgaria;"St. Cyril and St. Methodius" University of Veliko Tarnovo, Department of Information Technologies, 3 Architect Georgi Kozarov Street, Veliko Tarnovo, Bulgaria

  • Venue:
  • Data & Knowledge Engineering
  • Year:
  • 2008

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Abstract

Collaborative filtering aims to automate the process of organizing and recommending information to users. This process consists of predicting the user rating of a given item based on other users' ratings. We propose a new algorithm for tackling this problem based on discovering the functional error-correcting dependencies in a dataset by using the fractal dimension. We experimentally evaluate our algorithm and compare it to some of the baseline schemes. The experimental results presented in this paper prove that our approach improves the accuracy and the performance of the filtering.