On the Quantification of Missing Value Impact on Voting Advice Applications

Marilena Agathokleous, Nicolas Tsapatsoulis, Ioannis Katakis

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

5 Citations (Scopus)

Abstract

Voting Advice Application (VAA) is a web application that recommends a candidate or a party to a voter. From an online questionnaire, which voters and candidates are called to answer, the VAA proposes to each individual voter the candidate who replied like him/her. It is very important the voters to reply in all questions of the questionnaire, because every question has its meaning and is responding to the political position of a each party. Missing values might mislead the VAA and impede it to have complete knowledge about the voter, as a result to offer him/her the wrong candidate. In this paper we quantitatively investigate the effect of missing values in VAAs by examining the impact of the number of missing values to different methods of voting prediction. For our experiment we have used the data obtained from the May parliamentary elections in Greece in 2012. The corresponding dataset is made freely available to other researchers working in the areas of VAA and recommender systems through the Web.

Original languageEnglish
Title of host publicationEngineering Applications of Neural Networks - 14th International Conference, EANN 2013, Proceedings
PublisherSpringer Verlag
Pages496-505
Number of pages10
EditionPART 1
ISBN (Print)9783642410123
DOIs
Publication statusPublished - 1 Jan 2013
Event14th International Conference on Engineering Applications of Neural Networks, EANN 2013 - Halkidiki, Greece
Duration: 13 Sep 201316 Sep 2013

Publication series

NameCommunications in Computer and Information Science
NumberPART 1
Volume383 CCIS
ISSN (Print)1865-0929

Conference

Conference14th International Conference on Engineering Applications of Neural Networks, EANN 2013
CountryGreece
CityHalkidiki
Period13/09/1316/09/13

Keywords

  • classifiers
  • Missing values
  • recommender systems
  • voting advice applications

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  • Cite this

    Agathokleous, M., Tsapatsoulis, N., & Katakis, I. (2013). On the Quantification of Missing Value Impact on Voting Advice Applications. In Engineering Applications of Neural Networks - 14th International Conference, EANN 2013, Proceedings (PART 1 ed., pp. 496-505). (Communications in Computer and Information Science; Vol. 383 CCIS, No. PART 1). Springer Verlag. https://doi.org/10.1007/978-3-642-41013-0_51