A Dialogue-Based Information Retrieval Assistant Using Shallow NLP Techniques in Online Sales Domains

  • Authors:

  • Harksoo Kim;Choong-Nyoung Seon;Jungyun Seo

  • Affiliations:

  • The authors are with Diquest Inc., 7F, Sindo B/D, 1604-22, Seocho-dong, Seocho-gu, Seoul, 137--070, Korea. E-mail: hskim@diquest.com, E-mail: wilowisp@diquest.com,;The authors are with Diquest Inc., 7F, Sindo B/D, 1604-22, Seocho-dong, Seocho-gu, Seoul, 137--070, Korea. E-mail: hskim@diquest.com, E-mail: wilowisp@diquest.com,;The author is with the Dept. of Computer Science and Program of Integrated Biotechnology, Sogang University, Sinsu-dong 1, Mapo-gu, Seoul, 121--742, Korea. E-mail: seojy@ccs.sogang.ac.kr

  • Venue:
  • IEICE - Transactions on Information and Systems
  • Year:
  • 2005

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Abstract

Most of commercial websites provide customers with menu-driven navigation and keyword search. However, these inconvenient interfaces increase the number of mouse clicks and decrease customers' interest in surfing the websites. To resolve the problem, we propose an information retrieval assistant using a natural language interface in online sales domains. The information retrieval assistant has a client-server structure; a system connector and a NLP (natural language processing) server. The NLP server performs a linguistic analysis of users' queries with the help of coordinated NLP agents that are based on shallow NLP techniques. After receiving the results of the linguistic analysis from the NLP server, the system connector interacts with outer information provision systems such as conventional information retrieval systems and relational database management systems according to the analysis results. Owing to the client-server structure, we can easily add other information provision systems to the information retrieval assistant with trivial modifications of the NLP server. In addition, the information retrieval assistant guarantees fast responses because it uses shallow NLP techniques. In the preliminary experiment, as compared to the menu-driven system, we found that the information retrieval assistant could reduce the bothersome tasks such as menu selecting and mouse clicking because it provides a convenient natural language interface.