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Anticipatory search: using context to initiate search

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SIGIR '12: Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval

Pages 1035 - 1036

https://doi.org/10.1145/2348283.2348456

Published: 12 August 2012 Publication History

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Abstract

Identifying content for which a user may search has a variety of applications, including ranking and recommendation. In this poster, we examine how pre-search context can be used to predict content that the user will seek before they have even specified a search query. We call this anticipatory search. Using a log-based approach, we compare different methods for predicting the content to be searched using different attributes of the pre-query context and behavioral signals from previous visitors to the most recent browse URL. Each method covers different cases and shows promise for query-free anticipatory search on the Web.

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Cited By

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Jones WCapra RCzerwinski MDinneen JGwizdka JKaradkar U(2024)PIM 2024: The Information We Need, When We Need It…: As We Get Ever Closer, Is this Ideal Still Ideal?Proceedings of the 2024 Conference on Human Information Interaction and Retrieval10.1145/3627508.3638333(438-440)Online publication date: 10-Mar-2024
https://dl.acm.org/doi/10.1145/3627508.3638333
Ros KJin MLevine JZhai CYoshioka MKiseleva JAliannejadi M(2023)Retrieving Webpages Using Online DiscussionsProceedings of the 2023 ACM SIGIR International Conference on Theory of Information Retrieval10.1145/3578337.3605139(159-168)Online publication date: 9-Aug-2023
https://dl.acm.org/doi/10.1145/3578337.3605139
Bhattacharya MLamkhede S(2022)Augmenting Netflix Search with In-Session Adapted RecommendationsProceedings of the 16th ACM Conference on Recommender Systems10.1145/3523227.3547407(542-545)Online publication date: 12-Sep-2022
https://dl.acm.org/doi/10.1145/3523227.3547407
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Index Terms

Anticipatory search: using context to initiate search
1. Information systems
  1. Information retrieval

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Published In

SIGIR '12: Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval

August 2012

1236 pages

ISBN:9781450314725

DOI:10.1145/2348283

General Chair:
William Hersh
Oregon Health & Science University, USA
,
Program Chairs:
Jamie Callan
Carnegie Mellon University, USA
,
Yoelle Maarek
Yahoo! Research, Israel
,
Mark Sanderson
Royal Melbourne Institute of Technology, Australia

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 12 August 2012

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SIGIR '12: The 35th International ACM SIGIR conference on research and development in Information Retrieval

August 12 - 16, 2012

Oregon, Portland, USA

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

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Jones WCapra RCzerwinski MDinneen JGwizdka JKaradkar U(2024)PIM 2024: The Information We Need, When We Need It…: As We Get Ever Closer, Is this Ideal Still Ideal?Proceedings of the 2024 Conference on Human Information Interaction and Retrieval10.1145/3627508.3638333(438-440)Online publication date: 10-Mar-2024
https://dl.acm.org/doi/10.1145/3627508.3638333
Ros KJin MLevine JZhai CYoshioka MKiseleva JAliannejadi M(2023)Retrieving Webpages Using Online DiscussionsProceedings of the 2023 ACM SIGIR International Conference on Theory of Information Retrieval10.1145/3578337.3605139(159-168)Online publication date: 9-Aug-2023
https://dl.acm.org/doi/10.1145/3578337.3605139
Bhattacharya MLamkhede S(2022)Augmenting Netflix Search with In-Session Adapted RecommendationsProceedings of the 16th ACM Conference on Recommender Systems10.1145/3523227.3547407(542-545)Online publication date: 12-Sep-2022
https://dl.acm.org/doi/10.1145/3523227.3547407
Jacucci GDaee PVuong TAndolina SKlouche KSjöberg MRuotsalo TKaski S(2021)Entity Recommendation for Everyday Digital TasksACM Transactions on Computer-Human Interaction10.1145/345891928:5(1-41)Online publication date: 20-Aug-2021
https://dl.acm.org/doi/10.1145/3458919
Smith CRieh SAzzopardi LHalvey MRuthven IJoho HMurdock VQvarfordt P(2019)Knowledge-Context in Search SystemsProceedings of the 2019 Conference on Human Information Interaction and Retrieval10.1145/3295750.3298940(55-62)Online publication date: 8-Mar-2019
https://dl.acm.org/doi/10.1145/3295750.3298940
Andolina SOrso VSchneider HKlouche KRuotsalo TGamberini LJacucci GKoskinen ILim YCerratto-Pargman TChow KOdom W(2018)Investigating Proactive Search Support in ConversationsProceedings of the 2018 Designing Interactive Systems Conference10.1145/3196709.3196734(1295-1307)Online publication date: 8-Jun-2018
https://dl.acm.org/doi/10.1145/3196709.3196734
Koskela MLuukkonen PRuotsalo TSjÖberg MFloréen P(2018)Proactive Information Retrieval by Capturing Search Intent from Primary Task ContextACM Transactions on Interactive Intelligent Systems10.1145/31509758:3(1-25)Online publication date: 5-Jul-2018
https://dl.acm.org/doi/10.1145/3150975
Taramigkou MApostolou DMentzas G(2018)Leveraging exploratory search with personality traits and interactional contextInformation Processing and Management: an International Journal10.1016/j.ipm.2018.04.00154:4(609-629)Online publication date: 1-Jul-2018
https://dl.acm.org/doi/10.1016/j.ipm.2018.04.001
Van Gysel CMitra BVenanzi MRosemarin RKukla GGrudzien PCancedda NLim EWinslett MSanderson MFu ASun JCulpepper SLo EHo JDonato DAgrawal RZheng YCastillo CSun ATseng VLi C(2017)Reply WithProceedings of the 2017 ACM on Conference on Information and Knowledge Management10.1145/3132847.3132979(327-336)Online publication date: 6-Nov-2017
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Benetka JBalog KNørvåg Kde Rijke MShokouhi MTomkins AZhang M(2017)Anticipating Information Needs Based on Check-in ActivityProceedings of the Tenth ACM International Conference on Web Search and Data Mining10.1145/3018661.3018679(41-50)Online publication date: 2-Feb-2017
https://dl.acm.org/doi/10.1145/3018661.3018679
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Predicting Search Intent Based on Pre-Search Context

Improving Ranking Consistency for Web Search by Leveraging a Knowledge Base and Search Logs

Identifying popular search goals behind search queries to improve web search ranking

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