LDA-based Volunteer Opportunity Recommendation System - a Case Study in Senior Online Social Network

Abstract

According to the World Giving Index published by the Charities Aid Foundation nearly 1/5 people of the world population do volunteer service during their free time and this number is on the rise every years This has led to an increase in the number of nonprofit organizations and volunteer opportunities and it is hence becoming increasingly difficult for users interested in volunteering to choose a suitable opportunity from such a massive database This research tried to use the latent Dirichlet distribution (LDA) model to construct triangular relations among volunteer opportunities volunteer types and users We chose seniors as the target of our case study to build a volunteer opportunity recommendation system which assists seniors in making decisions when choosing volunteer opportunities This research developed an LDA-based volunteer opportunity recommendation system that constructs triangular relations among volunteer opportunities volunteer types and users In addition to LDA we take temporal and geographical constraints and social behavior in a senior-focused online social network into account to assist seniors in decision making when choosing volunteer opportunities For the experiment evaluation we used ten-fold cross-validation to test and evaluate recommendation models in three different dataset we collected We compared the three recommendation methods to observe their performance namely LDA model category-based and traditional collaborative filtering According to experimental results LDA model had the best performance in accuracy and category-based and collaborative filtering were neck and neck But only for sparse dataset category-based outperformed collaborative filtering Furthermore we investigated whether our method improved the performance of recommendation models by considering social information and temporal and geographical constraints Results showed that when considering temporal and geographical constraints the performance significantly improved which indicated that temporal and geographical constraints were important factors when recommending volunteer opportunities to users However social information slightly improved performance but the effect was not significant This research targeted seniors for our case study and developed a LDA-based volunteer opportunity recommendation system which used historical volunteer opportunities which the user had participated in the past and social behavior on the online social network to build recommendation models to assist seniors in decision making when choosing volunteer opportunities

Date of Award	2015 Aug 23
Original language	English
Supervisor	Jung-Hsien Chiang (Supervisor)