The Open Cybernetics & Systemics Journal

2014, 8 : 645-650
Published online 2014 December 31. DOI: 10.2174/1874110X01408010645
Publisher ID: TOCSJ-8-645

Question Recommendation Mechanism under Q&A Community based on LDA Model

Caiyin Wang , Lin Cui , Baosheng Yang and Xiaoyin Wu
Intelligent Information Processing Laboratory, Suzhou University, Suzhou, Anhui, 234000, China.

ABSTRACT

Aiming at the questions not answered timely under Q&A community, a kind of questions recommendation method based on LDA (Latent Dirichlet Allocation) topic model is proposed, which fully utilizes personalized information of users under Q&A community. The interests distributions of users are expressed through using LDA model and according to the interests distributions of users, questions recommendation lists are calculated out at last. The proposed method can recommend the unsolved problems to users who are interested in these questions, which makes these questions be solved out as soon as possible, and promotes information dissemination and knowledge sharing under Q&A community. Experimental results show that the proposed questions recommendation method based on LDA not only discoveries the unsolved questions quickly, but also recommends the most suitable answers to users compared with PLSA, KL-divergence and Cosine similarity.

Keywords:

Latent dirichlet allocation, Q & A community, question recommendation, questions recommendation lists.