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

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.
Type de document :
Communication dans un congrès
Harris Papadopoulos; Andreas S. Andreou; Lazaros Iliadis; Ilias Maglogiannis. 9th Artificial Intelligence Applications and Innovations (AIAI), Sep 2013, Paphos, Greece. Springer, IFIP Advances in Information and Communication Technology, AICT-412, pp.20-29, 2013, Artificial Intelligence Applications and Innovations. 〈10.1007/978-3-642-41142-7_3〉
Liste complète des métadonnées

Littérature citée [24 références]  Voir  Masquer  Télécharger

https://hal.inria.fr/hal-01459677
Contributeur : Hal Ifip <>
Soumis le : mardi 7 février 2017 - 13:18:33
Dernière modification le : vendredi 1 décembre 2017 - 01:16:33
Document(s) archivé(s) le : lundi 8 mai 2017 - 14:15:15

Fichier

978-3-642-41142-7_3_Chapter.pd...
Fichiers produits par l'(les) auteur(s)

Licence


Distributed under a Creative Commons Paternité 4.0 International License

Identifiants

Citation

Marilena Agathokleous, Nicolas Tsapatsoulis. Voting Advice Applications: Missing Value Estimation Using Matrix Factorization and Collaborative Filtering. Harris Papadopoulos; Andreas S. Andreou; Lazaros Iliadis; Ilias Maglogiannis. 9th Artificial Intelligence Applications and Innovations (AIAI), Sep 2013, Paphos, Greece. Springer, IFIP Advances in Information and Communication Technology, AICT-412, pp.20-29, 2013, Artificial Intelligence Applications and Innovations. 〈10.1007/978-3-642-41142-7_3〉. 〈hal-01459677〉

Partager

Métriques

Consultations de la notice

91

Téléchargements de fichiers

112