Retrieving good, better, and best answers to questions in advertisements

Question-Answering (QA) service is a growing area of research study, and commercial QA systems have recently been developed. We are motivated to provide complementary QA service that answers questions in advertisements (ads). These days with almost all businesses online, potential buyers who search for merchandises to purchase through the Internet are also flourishing. When a Web user looks for products online, he may have many questions on his mind for which he would be eager to receive answers prior to finalizing his purchasing decision. Although some ads Web sites are complemented with FAQs, their QA services either are non-existent or do not provide answers to inquires in real time automatically. We address these problems by answering user's questions such as "Which is the cheapest car?", "Are there any entry-level, software developer positions?", etc., spontaneously in real time. Existing general-purpose QA systems, such as Ask.com, provide answers to a user's question Q in a list format. A more sophisticated approach is to order the answers to Q according to their degrees of relevance to Q. We propose a QA system which deals with the challenge of interpreting users' questions and retrieves correct, as well as partially-matched ranked, answers. Experimental results have verified that the proposed QA system is highly accurate in answering users' questions on car ads.