JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE) ›› 2021, Vol. 56 ›› Issue (5): 76-84.doi: 10.6040/j.issn.1671-9352.1.2020.019

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Pseudo-relevance feedback method based on locational relationship in document

WANG Xue-yan1,2,3, HE Ting-ting1,2,3*, HUANG Xiang4, WANG Jun-mei5, PAN Min6   

  1. 1. Hubei Provincial Key Laboratory of Artificial Intelligence and Smart Learning, Wuhan 430070, Hubei, China;
    2. School of Computer, Central China Normal University, Wuhan 430070, Hubei, China;
    3. National Language Resources Monitor &
    Research Center for Network Media, Wuhan 430070, Hubei, China;
    4. National Engineering Research Center for E-Learning, Central China Normal University, Wuhan 430070, Hubei, China;
    5. School of Mathematics and Statistics, Central China Normal University, Wuhan 430070, Hubei, China;
    6. School of Computer and Information Engineering, Hubei Normal University, Huangshi 435000, Hubei, China
  • Published:2021-05-13

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Abstract: This paper proposes a location-based Rocchio framework(LRoc), with three variants. The method uses different kernel functions to model the term location in the feedback documents, obtains the importance information from the locations of candidate expansion terms, and integrates it into the classic Rocchio model. When selecting and evaluating the candidate expansion terms, this method not only considers term frequency, but also considers the influence of term location, which helps to obtain the expansion terms that are more likely to be relevant to the query. Finally, a series of experiments are performed on five standard text REtrieval conference(TREC)datasets. The proposed three models(LRoc1, LRoc2 and LRoc3)based on the LRoc framework all have got significant improvements over the baseline model in terms of the mean average precision(MAP)and precision at position 20(P@20)indicators.

Key words: pseudo-relevance feedback, locational relationship, query expansion

CLC Number: 

  • TP391
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