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Selecting Discriminative Terms for Relevance Model

Published: 18 July 2019 Publication History

Abstract

Pseudo-relevance feedback based on the relevance model does not take into account the inverse document frequency of candidate terms when selecting expansion terms. As a result, common terms are often included in the expanded query constructed by this model. We propose three possible extensions of the relevance model that address this drawback. Our proposed extensions are simple to compute and are independent of the base retrieval model. Experiments on several TREC news and web collections show that the proposed modifications yield significantly better MAP, precision, NDCG, and recall values than the original relevance model as well as its two recently proposed state-of-the-art variants.

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Cited By

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  • (2022)ColBERT-PRF: Semantic Pseudo-Relevance Feedback for Dense Passage and Document RetrievalACM Transactions on the Web10.1145/357240517:1(1-39)Online publication date: 22-Nov-2022
  • (2022)A Comparison between Term-Independence Retrieval Models for Ad Hoc RetrievalACM Transactions on Information Systems10.1145/348361240:3(1-37)Online publication date: 31-Jul-2022
  • (2022)A retrieval model family based on the probability ranking principle for ad hoc retrievalJournal of the Association for Information Science and Technology10.1002/asi.2461973:8(1140-1154)Online publication date: 5-Feb-2022
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cover image ACM Conferences
SIGIR'19: Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval
July 2019
1512 pages
ISBN:9781450361729
DOI:10.1145/3331184
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 18 July 2019

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Author Tags

  1. discriminative terms
  2. query expansion
  3. relevance feedback

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SIGIR '19
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SIGIR'19 Paper Acceptance Rate 84 of 426 submissions, 20%;
Overall Acceptance Rate 792 of 3,983 submissions, 20%

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Cited By

View all
  • (2022)ColBERT-PRF: Semantic Pseudo-Relevance Feedback for Dense Passage and Document RetrievalACM Transactions on the Web10.1145/357240517:1(1-39)Online publication date: 22-Nov-2022
  • (2022)A Comparison between Term-Independence Retrieval Models for Ad Hoc RetrievalACM Transactions on Information Systems10.1145/348361240:3(1-37)Online publication date: 31-Jul-2022
  • (2022)A retrieval model family based on the probability ranking principle for ad hoc retrievalJournal of the Association for Information Science and Technology10.1002/asi.2461973:8(1140-1154)Online publication date: 5-Feb-2022
  • (2021)On the Orthogonality of Bias and Utility in Ad hoc RetrievalProceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3404835.3463110(1748-1752)Online publication date: 11-Jul-2021
  • (2021)QA4PRF: A Question Answering Based Framework for Pseudo Relevance FeedbackIEEE Access10.1109/ACCESS.2021.31186009(139303-139314)Online publication date: 2021

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