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Towards natural question guided search

Published: 26 April 2010 Publication History

Abstract

Web search is generally motivated by an information need. Since asking well-formulated questions is the fastest and the most natural way to obtain information for human beings, almost all queries posed to search engines correspond to some underlying questions, which reflect the user's information need. Accurate determination of these questions may substantially improve the quality of search results and usability of search interfaces. In this paper, we propose a new framework for question-guided search, in which a retrieval system would automatically generate potentially interesting questions to users based on the search results of a query. Since the answers to such questions are known to exist in the search results, these questions can potentially guide users directly to the answers that they are looking for, eliminating the need to scan the documents in the result list. Moreover, in case of imprecise or ambiguous queries, automatically generated questions can naturally engage users into a feedback cycle to refine their information need and guide them towards their search goals. Implementation of the proposed strategy raises new challenges in content indexing, question generation, ranking and feedback. We propose new methods to address these challenges and evaluated them with a prototype system on a subset of Wikipedia. Evaluation results show the promise of this new question-guided search strategy.

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  • (2024)Let the LLMs Talk: Simulating Human-to-Human Conversational QA via Zero-Shot LLM-to-LLM InteractionsProceedings of the 17th ACM International Conference on Web Search and Data Mining10.1145/3616855.3635856(8-17)Online publication date: 4-Mar-2024
  • (2023)Learning to Select the Relevant History Turns in Conversational Question AnsweringWeb Information Systems Engineering – WISE 202310.1007/978-981-99-7254-8_26(334-348)Online publication date: 21-Oct-2023
  • (2022)CoSearcher: studying the effectiveness of conversational search refinement and clarification through user simulationInformation Retrieval Journal10.1007/s10791-022-09404-z25:2(209-238)Online publication date: 10-Mar-2022
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Published In

cover image ACM Other conferences
WWW '10: Proceedings of the 19th international conference on World wide web
April 2010
1407 pages
ISBN:9781605587998
DOI:10.1145/1772690

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 26 April 2010

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Author Tags

  1. interactive search
  2. query processing
  3. search interface

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  • Research-article

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WWW '10
WWW '10: The 19th International World Wide Web Conference
April 26 - 30, 2010
North Carolina, Raleigh, USA

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Overall Acceptance Rate 1,899 of 8,196 submissions, 23%

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Cited By

View all
  • (2024)Let the LLMs Talk: Simulating Human-to-Human Conversational QA via Zero-Shot LLM-to-LLM InteractionsProceedings of the 17th ACM International Conference on Web Search and Data Mining10.1145/3616855.3635856(8-17)Online publication date: 4-Mar-2024
  • (2023)Learning to Select the Relevant History Turns in Conversational Question AnsweringWeb Information Systems Engineering – WISE 202310.1007/978-981-99-7254-8_26(334-348)Online publication date: 21-Oct-2023
  • (2022)CoSearcher: studying the effectiveness of conversational search refinement and clarification through user simulationInformation Retrieval Journal10.1007/s10791-022-09404-z25:2(209-238)Online publication date: 10-Mar-2022
  • (2021)Studying the Effectiveness of Conversational Search Refinement Through User SimulationAdvances in Information Retrieval10.1007/978-3-030-72113-8_39(587-602)Online publication date: 27-Mar-2021
  • (2019)Attentive History Selection for Conversational Question AnsweringProceedings of the 28th ACM International Conference on Information and Knowledge Management10.1145/3357384.3357905(1391-1400)Online publication date: 3-Nov-2019
  • (2019)BERT with History Answer Embedding for Conversational Question AnsweringProceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3331184.3331341(1133-1136)Online publication date: 18-Jul-2019
  • (2018)Generating Synthetic Data for Neural Keyword-to-Question ModelsProceedings of the 2018 ACM SIGIR International Conference on Theory of Information Retrieval10.1145/3234944.3234964(51-58)Online publication date: 10-Sep-2018
  • (2017)What Do You Mean Exactly?Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval10.1145/3020165.3022149(345-348)Online publication date: 7-Mar-2017
  • (2015)Towards topic-to-question generationComputational Linguistics10.1162/COLI_a_0020641:1(1-20)Online publication date: 1-Mar-2015
  • (2014)Multimedia questions and answering using web data miningInternational Conference on Information Communication and Embedded Systems (ICICES2014)10.1109/ICICES.2014.7033845(1-4)Online publication date: Mar-2014
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