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Query rewriting using active learning for sponsored search

Published: 23 July 2007 Publication History

Abstract

Sponsored search is a major revenue source for search companies. Web searchers can issue any queries, while advertisement keywords are limited. Query rewriting technique effectively matches user queries with relevant advertisement keywords, thus increases the amount of web advertisements available. The match relevance is critical for clicks. In this study, we aim to improve query rewriting relevance. For this purpose, we use an active learning algorithm called Transductive Experimental Design to select the most informative samples to train the query rewriting relevance model. Experiments show that this approach significantly improves model accuracy and rewriting relevance.

References

[1]
Jones, B. Rey, O. Madani, and W. Greiner. Generating query substitutions. In Proceedings of WWW, Edinburgh, Scotland, 2006.
[2]
K. Yu, J. Bi, and V. Tresp. Active learning via transductive experimental design. In Proc. of the 23rd International Conference on Machine Learning, 2006.

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  • (2022)Knowledge Enhanced Multi-Interest Network for the Generation of Recommendation CandidatesProceedings of the 31st ACM International Conference on Information & Knowledge Management10.1145/3511808.3557114(3322-3331)Online publication date: 17-Oct-2022
  • (2020)OctopusProceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3397271.3401088(289-298)Online publication date: 25-Jul-2020
  • (2020)Meta-Learning for Query Conceptualization at Web ScaleProceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining10.1145/3394486.3403357(3064-3073)Online publication date: 23-Aug-2020
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    cover image ACM Conferences
    SIGIR '07: Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
    July 2007
    946 pages
    ISBN:9781595935977
    DOI:10.1145/1277741
    Permission to make digital or hard copies of all or part 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 components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 23 July 2007

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    Author Tags

    1. active learning
    2. query rewriting
    3. sponsored search

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    SIGIR07
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    SIGIR07: The 30th Annual International SIGIR Conference
    July 23 - 27, 2007
    Amsterdam, The Netherlands

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

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    Cited By

    View all
    • (2022)Knowledge Enhanced Multi-Interest Network for the Generation of Recommendation CandidatesProceedings of the 31st ACM International Conference on Information & Knowledge Management10.1145/3511808.3557114(3322-3331)Online publication date: 17-Oct-2022
    • (2020)OctopusProceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3397271.3401088(289-298)Online publication date: 25-Jul-2020
    • (2020)Meta-Learning for Query Conceptualization at Web ScaleProceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining10.1145/3394486.3403357(3064-3073)Online publication date: 23-Aug-2020
    • (2020)Conversations with Documents: An Exploration of Document-Centered AssistanceProceedings of the 2020 Conference on Human Information Interaction and Retrieval10.1145/3343413.3377971(43-52)Online publication date: 14-Mar-2020
    • (2020)Acquiring New Definitions of EntitiesArtificial Intelligence for Customer Relationship Management10.1007/978-3-030-52167-7_6(193-263)Online publication date: 8-Dec-2020
    • (2019)AiAdsProceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining10.1145/3292500.3330782(1881-1890)Online publication date: 25-Jul-2019
    • (2019)MOBIUSProceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining10.1145/3292500.3330651(2509-2517)Online publication date: 25-Jul-2019
    • (2015)Interpreting Advertiser Intent in Sponsored SearchProceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining10.1145/2783258.2788566(2177-2185)Online publication date: 10-Aug-2015
    • (2015)Sponsored Search AuctionsACM Transactions on Intelligent Systems and Technology10.1145/26681085:4(1-34)Online publication date: 23-Jan-2015
    • (2015)A general framework to resolve the MisMatch problem in XML keyword searchThe VLDB Journal — The International Journal on Very Large Data Bases10.1007/s00778-015-0386-124:4(493-518)Online publication date: 1-Aug-2015
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