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ABSTRACT

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.

REFERENCES

• 1: Adam Berger , Rich Caruana , David Cohn , Dayne Freitag , Vibhu Mittal, Bridging the lexical chasm: statistical approaches to answer-finding, Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrieval, p.192-199, July 24-28, 2000, Athens, Greece [doi>10.1145/345508.345576]
• 2: R. Besancoa, M. Embarck, and O. Ferret. Finding Answers in the Cedipe System by Extracting and Applying Linguistic Patterns. In Proc. of Evaluation of Multilingual and Multi-Modal Information Retrieval: the 7th Workshop of the CLEF, pages 395--404, 2006.
• 3: E. Brill, J. Lin, M. Banko, S. Dumais, and A. Ng. Data-Intensive Question Answering. In Proc. of the Text REtrieval Conference, pages 393--400, 2001.
• 4: Hang Cui , Min-Yen Kan , Tat-Seng Chua, Soft pattern matching models for definitional question answering, ACM Transactions on Information Systems (TOIS), v.25 n.2, p.8-es, April 2007 [doi>10.1145/1229179.1229182]
• 5: D. Ferres and H. Rodriguez. Experiments Adapting an Open-Domain Question Answering System to the Geographical Domain Using Scope-Based Resources. In Proc. of the 11th Conference of the European Chapter of the 57 Natural-Language Text, 2006.
• 6: Yi Luo , Xuemin Lin , Wei Wang , Xiaofang Zhou, Spark: top-k keyword query in relational databases, Proceedings of the 2007 ACM SIGMOD international conference on Management of data, June 11-14, 2007, Beijing, China [doi>10.1145/1247480.1247495]
• 7: Diego Mollá , José Luis Vicedo, Question Answering in Restricted Domains: An Overview, Computational Linguistics, v.33 n.1, p.41-61, March 2007 [doi>10.1162/coli.2007.33.1.41]
• 8: Marius Paşca, Lightweight web-based fact repositories for textual question answering, Proceedings of the sixteenth ACM conference on Conference on information and knowledge management, November 06-10, 2007, Lisbon, Portugal [doi>10.1145/1321440.1321455]
• 9: M. Pera, R. Qumsiyeh, M. Shaikh, and Y.-K. Ng. Retrieving Good, Better, and Best Answers to Questions in Advertisements. Technical report, Computer Science Department, Brigham Young University, November 2009.
• 10: Dragomir Radev , Weiguo Fan , Hong Qi , Harris Wu , Amardeep Grewal, Probabilistic question answering on the web, Proceedings of the 11th international conference on World Wide Web, May 07-11, 2002, Honolulu, Hawaii, USA [doi>10.1145/511446.511500]
• 11: E. Sang, G. Bouma, and M. de Rijke. Developing Offline Strategies for Answering Medical Questions. In Proc. of Workshop on QA in Restricted Domains, pages 41--45, 2005.
• 12: O. Tsur, M. de Rijke, and K. Simaan. BioGrapher: Biography Questions as a Restricted Domain Question Answering Task. In Proc. of ACL Workshop on QA in Restricted Domains, pages 23--30, 2004.
• 13: M. Vargas-Vera, E. Motta, and J. Domingue. AQUA: An Ontology-Driven Question Answering System. In Proc. of the 3rd MICAI, pages 468--477, 2004.

INDEX TERMS

Primary Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.4 Systems and Software
          Subjects: Question-answering (fact retrieval) systems**

General Terms:
Design, Languages, Measurement

Keywords:
partial matching, question answering, similarity measure