Searching Questions by Identifying Question Topic and Question Focus

This paper is concerned with the problem of question search. In question search, given a question as query, we are to return questions semantically equivalent or close to the queried question. In this paper, we propose to conduct question search by identifying question topic and question focus. More specifically, we first summarize questions in a data structure con- sisting of question topic and question focus. Then we model question topic and question focus in a language modeling framework for search. We also propose to use the MDL- based tree cut model for identifying question topic and question focus automatically. Expe- rimental results indicate that our approach of identifying question topic and question focus for search significantly outperforms the base- line methods such as Vector Space Model (VSM) and Language Model for Information Retrieval (LMIR).