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Anticipatory search: using context to initiate search

Published: 12 August 2012 Publication History

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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  • (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
  • (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
  • (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
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cover image ACM Conferences
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

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 12 August 2012

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Author Tags

  1. anticipatory search
  2. pre-search context
  3. web search

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

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  • (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
  • (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
  • (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
  • (2021)Entity Recommendation for Everyday Digital TasksACM Transactions on Computer-Human Interaction10.1145/345891928:5(1-41)Online publication date: 20-Aug-2021
  • (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
  • (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
  • (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
  • (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
  • (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
  • (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
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