Improving Question Retrieval in Community Question Answering Using World Knowledge

Community question answering (cQA), which providesa platform for people with diverse backgroundto share information and knowledge, hasbecome an increasingly popular research topic. Inthis paper, we focus on the task of question retrieval.The key problem of question retrieval is tomeasure the similarity between the queried questionsand the historical questions which have beensolved by other users. The traditional methodsmeasure the similarity based on the bag-of-words(BOWs) representation. This representation neithercaptures dependencies between related words, norhandles synonyms or polysemous words. In thiswork, we first propose a way to build a conceptthesaurus based on the semantic relations extractedfrom the world knowledge of Wikipedia. Then, wedevelop a unified framework to leverage these semanticrelations in order to enhance the questionsimilarity in the concept space. Experiments conductedon a real cQA data set show that with thehelp of Wikipedia thesaurus, the performance ofquestion retrieval is improved as compared to thetraditional methods.