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A Hybrid Information Retrieval Model Using Metadata and Text  

Yoo, Jeong-Mok (한국전자통신연구원 디지털홈연구단 인터넷서버그룹)
Myaeng, Sung-Hyon (한국정보통신대학교 공학부)
Kim, Sung-Soo (한국통신 비지니스부문 프로젝트 관리부)
Lee, Mann-Ho (충남대학교 전기정보통신공학부)
Publication Information
Journal of KIISE:Databases / v.34, no.3, 2007 , pp. 232-243 More about this Journal
Abstract
Metadata IR model has high precision and low recall because the query in Metadata IR model is strict that is, the query can express user information need exactly, while Full-text IR model has low precision and high recall because the query in Full-text IR model is a kind of simple keyword query which expresses user information need roughly. If user can translate one's information need into structured query well, the retrieval result will be improved. However, it is little possible to make relevant query without understanding characteristics of metadata. Unfortunately, most users do not interested in metadata, then they cannot construct well-made structured query. Amount of information contained in metadata is less than text information. In this paper, we suggest hybrid IR model using metadata and text which can provide users with lots of relevant documents by retrieving from metadata field and text field complementarily.
Keywords
Requirements Change Management; Requirements Change Management Process; Software Product Lines;
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