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ORCAS: 18 Million Clicked Query-Document Pairs for Analyzing Search

Authors:

Bodo BillerbeckAuthors Info & Claims

CIKM '20: Proceedings of the 29th ACM International Conference on Information & Knowledge Management

Pages 2983 - 2989

https://doi.org/10.1145/3340531.3412779

Published: 19 October 2020 Publication History

Abstract

Users of Web search engines reveal their information needs through queries and clicks, making click logs a useful asset for information retrieval. However, click logs have not been publicly released for academic use, because they can be too revealing of personally or commercially sensitive information. This paper describes a click data release related to the TREC Deep Learning Track document corpus. After aggregation and filtering, including a k -anonymity requirement, we find 1.4 million of the TREC DL URLs have 18 million connections to 10 million distinct queries. Our dataset of these queries and connections to TREC documents is of similar size to proprietary datasets used in previous papers on query mining and ranking. We perform some preliminary experiments using the click data to augment the TREC DL training data, offering by comparison: 28x more queries, with 49x more connections to 4.4x more URLs in the corpus. We present a description of the dataset's generation process, characteristics, use in ranking and other potential uses.

Supplementary Material

MP4 File (3340531.3412779.mp4)

Description of the ORCAS dataset: Open Resource for Click Analysis in Search. This is based on search log data, with aggregation, to identify query-URL pairs that were clicked by many users. The data can be used to improve search or for web mining such as finding related queries.

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Cited By

Azzopardi LBreuer TEngelmann BKreutz CMacAvaney SMaxwell DParry ARoegiest AWang XZerhoudi SSakai TIshita EOhshima HHasibi FMao JJose J(2024)SimIIR 3: A Framework for the Simulation of Interactive and Conversational Information RetrievalProceedings of the 2024 Annual International ACM SIGIR Conference on Research and Development in Information Retrieval in the Asia Pacific Region10.1145/3673791.3698427(197-202)Online publication date: 8-Dec-2024
https://dl.acm.org/doi/10.1145/3673791.3698427
Sharma ALi HLi XJiao JBaeza-Yates RBonchi F(2024)Optimizing Novelty of Top-k Recommendations using Large Language Models and Reinforcement LearningProceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining10.1145/3637528.3671618(5669-5679)Online publication date: 25-Aug-2024
https://dl.acm.org/doi/10.1145/3637528.3671618
Frew LNelson MWeigle MSerra ESpezzano F(2024)Retrogressive Document Manipulation of US Federal Environmental WebsitesProceedings of the 33rd ACM International Conference on Information and Knowledge Management10.1145/3627673.3679988(3762-3766)Online publication date: 21-Oct-2024
https://dl.acm.org/doi/10.1145/3627673.3679988
Show More Cited By

Index Terms

ORCAS: 18 Million Clicked Query-Document Pairs for Analyzing Search
1. Information systems
  1. Information retrieval
    1. Information retrieval query processing
      1. Query log analysis
    2. Retrieval models and ranking
  2. World Wide Web
    1. Web mining
      1. Web log analysis

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cover image ACM Conferences

CIKM '20: Proceedings of the 29th ACM International Conference on Information & Knowledge Management

October 2020

3619 pages

ISBN:9781450368599

DOI:10.1145/3340531

General Chairs:
Mathieu d'Aquin
DSI, Insight, NUI Galway, Ireland
,
Stefan Dietze
GESIS, Cologne, Germany, Heinrich-Heine-University Düsseldorf, Germany, L3S Research Center, Germany
,
Program Chairs:
Claudia Hauff
TU Delft, The Netherlands
,
Edward Curry
DSI, Insight, NUI Galway, Ireland
,
Philippe Cudre Mauroux
eXascale, University of Fribourg, Switzerland

Copyright © 2020 ACM.

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Published: 19 October 2020

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October 19 - 23, 2020

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Cited By

Azzopardi LBreuer TEngelmann BKreutz CMacAvaney SMaxwell DParry ARoegiest AWang XZerhoudi SSakai TIshita EOhshima HHasibi FMao JJose J(2024)SimIIR 3: A Framework for the Simulation of Interactive and Conversational Information RetrievalProceedings of the 2024 Annual International ACM SIGIR Conference on Research and Development in Information Retrieval in the Asia Pacific Region10.1145/3673791.3698427(197-202)Online publication date: 8-Dec-2024
https://dl.acm.org/doi/10.1145/3673791.3698427
Sharma ALi HLi XJiao JBaeza-Yates RBonchi F(2024)Optimizing Novelty of Top-k Recommendations using Large Language Models and Reinforcement LearningProceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining10.1145/3637528.3671618(5669-5679)Online publication date: 25-Aug-2024
https://dl.acm.org/doi/10.1145/3637528.3671618
Frew LNelson MWeigle MSerra ESpezzano F(2024)Retrogressive Document Manipulation of US Federal Environmental WebsitesProceedings of the 33rd ACM International Conference on Information and Knowledge Management10.1145/3627673.3679988(3762-3766)Online publication date: 21-Oct-2024
https://dl.acm.org/doi/10.1145/3627673.3679988
Vonásek JStraka MKrč RLasonová LEgorova EStraková JNáplava JHui Yang GWang HHan SHauff CZuccon GZhang Y(2024)CWRCzech: 100M Query-Document Czech Click Dataset and Its Application to Web Relevance RankingProceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3626772.3657851(1221-1231)Online publication date: 10-Jul-2024
https://dl.acm.org/doi/10.1145/3626772.3657851
Chen QGeng XRosset CBuractaon CLu JShen TZhou KXiong CGong YBennett PCraswell NXie XYang FTower BRao NDong AJiang WLiu ZLi MLiu CLi ZMajumder RNeville JOakley ARisvik KSimhadri HVarma MWang YYang LYang MZhang CChua TNgo CKumar RLauw HKa-Wei Lee R(2024)MS MARCO Web Search: A Large-scale Information-rich Web Dataset with Millions of Real Click LabelsCompanion Proceedings of the ACM Web Conference 202410.1145/3589335.3648327(292-301)Online publication date: 13-May-2024
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Khan ARashid USaadia AYasin A(2024)A Heuristic Multimedia Verticals Aggregated Search Approach and User Behavioral Analysis2024 International Conference on Engineering & Computing Technologies (ICECT)10.1109/ICECT61618.2024.10581027(1-6)Online publication date: 23-May-2024
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Krasakis AYates AKanoulas E(2023)Contextualizing and Expanding Conversational Queries without SupervisionACM Transactions on Information Systems10.1145/363262242:3(1-30)Online publication date: 17-Nov-2023
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