Title :
Clustering Online Poll Data: Towards a Voting Assistance System
Author :
Katakis, Ioannis ; Tsapatsoulis, Nicolas ; Triga, Vasiliki ; Tziouvas, C. ; Mendez, Fernando
Author_Institution :
Cyprus Univ. of Technol., Limassol, Cyprus
Abstract :
Voting advice applications (VAA) are very recently developed in order to aid users in deciding what to vote in elections. Every user is presented with a set of important issues and she is asked to submit her opinion by selecting one of a predefined set of answers (e.g. agree/disagree). The VAA gathers the same information for all candidates that are about to compete in the elections. Hence, it can provide recommendation to users: the candidates that agree with the user on these selected issues. In this paper, we propose a collaborating filtering approach for providing such suggestions. Like-minded users are clustered together based on their profiles (views on the selected issues) and voting recommendation is provided to a user by the members of the nearest (to her profile) cluster. We observe that this method produces more effective recommendations by utilizing two different measures: accuracy and weighted mean rank. Furthermore, the proposed method provides with important insight and summarization information about the electorate´s opinion. This research is based on new data gathered by the voting advice application Choose4Greece which was widely used for the most recent elections in Greece.
Keywords :
collaborative filtering; government data processing; pattern clustering; recommender systems; Choose4Greece; VAA; accuracy measure; collaborating filtering approach; online poll data clustering; profiles; vote recommendation systems; voting advice applications; voting assistance system; voting recommendation; weighted mean rank measure; Accuracy; Clustering algorithms; Educational institutions; Nominations and elections; Training; Vectors; Weight measurement; clustering; data mining; e-democracy; e-government; recommendation; vaa; voting advice applications;
Conference_Titel :
Semantic and Social Media Adaptation and Personalization (SMAP), 2012 Seventh International Workshop on
Conference_Location :
Luxembourg
Print_ISBN :
978-1-4673-4563-7
DOI :
10.1109/SMAP.2012.19
