Paper: Latent Semantic Tensor Indexing for Community-based Question Answering

ACL ID P13-2077
Title Latent Semantic Tensor Indexing for Community-based Question Answering
Venue Annual Meeting of the Association of Computational Linguistics
Session Short Paper
Year 2013
Authors

Retrieving similar questions is very important in community-based ques- tion answering(CQA). In this paper, we propose a unified question retrieval model based on latent semantic index- ing with tensor analysis, which can cap- ture word associations among different parts of CQA triples simultaneously. Thus, our method can reduce lexical chasm of question retrieval with the help of the information of question con- tent and answer parts. The experimen- tal result shows that our method out- performs the traditional methods.