An entropy-based query expansion approach for learning researchers' dynamic information needs

I. Chin Wu*, Guan Wei Chen, Jia Lien Hsu, Chun Yu Lin

*此作品的通信作者

研究成果: 雜誌貢獻期刊論文同行評審

3 引文 斯高帕斯(Scopus)

摘要

Literature survey is one of the most important steps in the process of academic research, allowing researchers to explore and understand topics. However, novice researchers without sufficient prior knowledge lack the skills to determine proper keywords for searching topics of choice. To tackle this problem, we propose an entropy-based query expansion with a reweighting (E-QE) approach to revise queries during the iterative retrieval process. We designed a series of experiments that consider the researcher's changing information needs during task execution. Three topic change situations are considered in this work: minor, moderate and dramatic topic changes. The simulation-based pseudo-relevance feedback technique is applied during the search process to evaluate the effectiveness of the proposed approach without the intervention of human effort. We measured the effectiveness of the TFIDF and E-QE approaches for different types of topic change situations. The results show that the proposed E-QE approach achieves better search results than the TFIDF, helping researchers to revise queries. The results also confirm that the E-QE approach is effective when considering the relevant and irrelevant pages during the relevance feedback process at different levels of topic change.

原文英語
頁(從 - 到)133-146
頁數14
期刊Knowledge-Based Systems
52
DOIs
出版狀態已發佈 - 2013 十一月 1

ASJC Scopus subject areas

  • 管理資訊系統
  • 軟體
  • 資訊系統與管理
  • 人工智慧

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