An Effective Approach for Party Recommendation in Voting Advice Application

Abstract

When it comes to the current political scenario the large number of political parties put voters, especially first time voters, women, youngsters etc., in confusing state regarding whom to vote for. To solve this issue of, Voting Advice Applications (VAAs) which are questionnaire based recommender systems are used. VAAs are online tools that suggest the user with the most suitable party based on answers to the policy based questions. Even though this is an active area of research in the western political scenario, the performance of the existing algorithms are not very appreciable. Also the existing works have not imparted the human decision making behavior in developing algorithms. This research work aims in proposing novel approaches based on the human decision making which can efficiently suggest suitable parties for the voters. Soft set and Fuzzy Soft Set are techniques that are found to be good in modeling human decision making as it supports parameterization and vagueness. The proposed work uses these techniques to develop algorithms that can effectively suggest the voter with a suitable party. The research is carried out in the domain of political scenario in Kerala, where this is the first research in the area of VAAs. The developed algorithms were evaluated on a data set collected from various parts of the state and found promising.