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The cluster hypothesis in information retrieval

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SIGIR '13: Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval

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https://doi.org/10.1145/2484028.2484192

Published: 28 July 2013 Publication History

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Abstract

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Reference

[1]

C. J. van Rijsbergen. Information Retrieval. Butterworths, second edition, 1979.

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Moreno AGuimarães Pedronette D(2024)Unsupervised Dual-Layer Aggregation for Feature Fusion on Image Retrieval Tasks2024 37th SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI)10.1109/SIBGRAPI62404.2024.10716343(1-6)Online publication date: 30-Sep-2024
https://doi.org/10.1109/SIBGRAPI62404.2024.10716343
Liu TZhang XZhang ZWang YLi QZhang SLiu T(2023)Enhancing Table Retrieval with Dual Graph RepresentationsMachine Learning and Knowledge Discovery in Databases: Research Track10.1007/978-3-031-43421-1_7(107-123)Online publication date: 18-Sep-2023
https://doi.org/10.1007/978-3-031-43421-1_7
MacAvaney STonellotto NMacdonald CAl Hasan MXiong L(2022)Adaptive Re-Ranking with a Corpus GraphProceedings of the 31st ACM International Conference on Information & Knowledge Management10.1145/3511808.3557231(1491-1500)Online publication date: 17-Oct-2022
https://dl.acm.org/doi/10.1145/3511808.3557231
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Index Terms

The cluster hypothesis in information retrieval
1. Information systems
  1. Information retrieval
    1. Retrieval models and ranking

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Published In

SIGIR '13: Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval

July 2013

1188 pages

ISBN:9781450320344

DOI:10.1145/2484028

General Chairs:
Gareth J.F. Jones
Dublin City University, Ireland
,
Páraic Sheridan
Dublin City University, Ireland
,
Program Chairs:
Diane Kelly
University of North Carolina, Chapel Hill, USA
,
Maarten de Rijke
University of Amsterdam, The Netherlands
,
Tetsuya Sakai
Microsoft Research Asia, China

Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

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Published: 28 July 2013

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SIGIR '13

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SIGIR

SIGIR '13: The 36th International ACM SIGIR conference on research and development in Information Retrieval

July 28 - August 1, 2013

Dublin, Ireland

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SIGIR '13 Paper Acceptance Rate 73 of 366 submissions, 20%;

Overall Acceptance Rate 792 of 3,983 submissions, 20%

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Moreno AGuimarães Pedronette D(2024)Unsupervised Dual-Layer Aggregation for Feature Fusion on Image Retrieval Tasks2024 37th SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI)10.1109/SIBGRAPI62404.2024.10716343(1-6)Online publication date: 30-Sep-2024
https://doi.org/10.1109/SIBGRAPI62404.2024.10716343
Liu TZhang XZhang ZWang YLi QZhang SLiu T(2023)Enhancing Table Retrieval with Dual Graph RepresentationsMachine Learning and Knowledge Discovery in Databases: Research Track10.1007/978-3-031-43421-1_7(107-123)Online publication date: 18-Sep-2023
https://doi.org/10.1007/978-3-031-43421-1_7
MacAvaney STonellotto NMacdonald CAl Hasan MXiong L(2022)Adaptive Re-Ranking with a Corpus GraphProceedings of the 31st ACM International Conference on Information & Knowledge Management10.1145/3511808.3557231(1491-1500)Online publication date: 17-Oct-2022
https://dl.acm.org/doi/10.1145/3511808.3557231
Sutanto TNayak R(2021)Fast Knowledge Discovery in Social Media Data using Clustering via Ranking2021 9th International Conference on Cyber and IT Service Management (CITSM)10.1109/CITSM52892.2021.9588866(1-8)Online publication date: 22-Sep-2021
https://doi.org/10.1109/CITSM52892.2021.9588866
Jung AHero III AMara AJahromi SHeimowitz AEldar Y(2019)Semi-Supervised Learning in Network-Structured Data via Total Variation MinimizationIEEE Transactions on Signal Processing10.1109/TSP.2019.295359367:24(6256-6269)Online publication date: 15-Dec-2019
https://doi.org/10.1109/TSP.2019.2953593
Sutanto TNayak R(2018)Fine-grained document clustering via ranking and its application to social media analyticsSocial Network Analysis and Mining10.1007/s13278-018-0508-z8:1Online publication date: 7-Apr-2018
https://doi.org/10.1007/s13278-018-0508-z
Yu HJatowt ABlanco RJoho HJose JChen LYuan Fde Rijke MShokouhi MTomkins AZhang M(2017)A Concise Integer Linear Programming Formulation for Implicit Search Result DiversificationProceedings of the Tenth ACM International Conference on Web Search and Data Mining10.1145/3018661.3018710(191-200)Online publication date: 2-Feb-2017
https://dl.acm.org/doi/10.1145/3018661.3018710

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Exploring the cluster hypothesis, and cluster-based retrieval, over the web

The correlation between cluster hypothesis tests and the effectiveness of cluster-based retrieval

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Testing the cluster hypothesis in distributed information retrieval

Exploring the cluster hypothesis, and cluster-based retrieval, over the web

The correlation between cluster hypothesis tests and the effectiveness of cluster-based retrieval

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