Semantic Link Analysis for Finding Answer Experts

Recommending unanswered questions to answer experts is an important mechanism in User-Interactive Question Answering (UIQA) services, which is helpful to reduce asker’s waiting time and obtain high-quality answers. In this project, we propose to study the problem of identifying answer experts in UIQA services with semantic information extracted from user interaction behaviors. We first construct the user question-answer interaction graph through direct semantic links and latent links extracted from the records of question sessions and user profiles in UIQA services. After that, two expert-finding approaches are produced by applying the semantic information to a link analysis method called propagation and the language model. We propose to conduct this research in three phases. The first phrase will focus on building user question-answer interaction graph. Exploring the link analysis and language model approaches for expert finding will be conducted in Phase 2. Finally, we will evaluate the proposed model in Phase 3.