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View all- Joseph MRavana S(2024)Reliable Information Retrieval Systems Performance Evaluation: A ReviewIEEE Access10.1109/ACCESS.2024.337723912(51740-51751)Online publication date: 2024
From Cluster Ranking to Document Ranking
Pages 2137 - 2141
Abstract
The common approach of using clusters of similar documents for ad hoc document retrieval is to rank the clusters in response to the query; then, the cluster ranking is transformed to document ranking. We present a novel supervised approach to transform cluster ranking to document ranking. The approach allows to simultaneously utilize different clusterings and the resultant cluster rankings; this helps to improve the modeling of the document similarity space. Empirical evaluation shows that using our approach results in performance that substantially transcends the state-of-the-art in cluster-based document retrieval.
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Index Terms
- From Cluster Ranking to Document Ranking
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Published In
July 2022
3569 pages
ISBN:9781450387323
DOI:10.1145/3477495
- General Chairs:
- Enrique Amigo,
- Pablo Castells,
- Julio Gonzalo,
- Program Chairs:
- Ben Carterette,
- J. Shane Culpepper,
- Gabriella Kazai
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Publication History
Published: 07 July 2022
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- VATAT
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SIGIR '22
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SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval
July 11 - 15, 2022
Madrid, Spain
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Overall Acceptance Rate 792 of 3,983 submissions, 20%
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View all- Joseph MRavana S(2024)Reliable Information Retrieval Systems Performance Evaluation: A ReviewIEEE Access10.1109/ACCESS.2024.337723912(51740-51751)Online publication date: 2024
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