Author:
Chou Shihchieh,Dai Zhangting
Abstract
Purpose
Conventional studies mainly classify a term’s appearance in the retrieved documents as either relevant or irrelevant for application. The purpose of this paper is to differentiate the term’s appearances in the retrieved documents in more detailed situations to generate relevance information and demonstrate the applicability of the derived information in combination with current methods of query expansion.
Design/methodology/approach
A method was designed first to utilize the derived information owing to term appearance differentiation within a conventional query expansion approach that has been proven as an effective technology in the enhancement of information retrieval. Then, an information retrieval system was developed to demonstrate the realization and sustain the study of the method. Formal tests were conducted to examine the distinguishing capability of the proposed information utilized in the method.
Findings
The experimental results show that substantial differences in performances can be achieved between the proposed method and the conventional query expansion method alone.
Practical implications
Since the proposed information resides at the bottom of the information hierarchy of relevance feedback, any technology regarding the application of relevance feedback information could consider the utilization of this piece of information.
Originality/value
The importance of the study is the disclosure of the applicability of the proposed information beyond current usage of term appearances in relevant/irrelevant documents and the initiation of a query expansion technology in the application of this information.
Subject
Library and Information Sciences,Computer Science Applications,Information Systems
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3. Chen, Z. and Lu, Y. (2010), “Using text classification method in relevance feedback”, in Nguyen, N., Le, M. and Świątek, J. (Eds), Intelligent Information and Database Systems, Springer, Berlin and Heidelberg, pp. 441-449.
Cited by
2 articles.
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