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Voting Advice Applications: Missing Value Estimation Using Matrix Factorization and Collaborative Filtering

  • Marilena Agathokleous
  • Nicolas Tsapatsoulis
Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT, volume 412)

Abstract

A Voting Advice Application (VAA) is a web application that recommends to a voter the party or the candidate, who replied like him/her in an online questionnaire. Every question is responding to the political positions of each party. If the voter fails to answer some questions, it is likely the VAA to offer him/her the wrong candidate. Therefore, it is necessary to inspect the missing data (not answered questions) and try to estimate them. In this paper we formulate the VAA missing value problem and investigate several different approaches of collaborative filtering to tackle it. The evaluation of the proposed approaches was done by using the data obtained from the Cypriot presidential elections of February 2013 and the parliamentary elections in Greece in May, 2012. The corresponding datasets are made freely available to other researchers working in the areas of VAA and recommender systems through the Web.

Keywords

Missing values collaborative filtering recommender systems voting advice applications 

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Copyright information

© IFIP International Federation for Information Processing 2013

Authors and Affiliations

  • Marilena Agathokleous
    • 1
  • Nicolas Tsapatsoulis
    • 1
  1. 1.LimassolCyprus

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