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Building bridges for web query classification

Published: 06 August 2006 Publication History

Abstract

Web query classification (QC) aims to classify Web users' queries, which are often short and ambiguous, into a set of target categories. QC has many applications including page ranking in Web search, targeted advertisement in response to queries, and personalization. In this paper, we present a novel approach for QC that outperforms the winning solution of the ACM KDDCUP 2005 competition, whose objective is to classify 800,000 real user queries. In our approach, we first build a bridging classifier on an intermediate taxonomy in an offline mode. This classifier is then used in an online mode to map user queries to the target categories via the above intermediate taxonomy. A major innovation is that by leveraging the similarity distribution over the intermediate taxonomy, we do not need to retrain a new classifier for each new set of target categories, and therefore the bridging classifier needs to be trained only once. In addition, we introduce category selection as a new method for narrowing down the scope of the intermediate taxonomy based on which we classify the queries. Category selection can improve both efficiency and effectiveness of the online classification. By combining our algorithm with the winning solution of KDDCUP 2005, we made an improvement by 9.7% and 3.8% in terms of precision and F1 respectively compared with the best results of KDDCUP 2005.

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cover image ACM Conferences
SIGIR '06: Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
August 2006
768 pages
ISBN:1595933697
DOI:10.1145/1148170
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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Publication History

Published: 06 August 2006

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Author Tags

  1. KDDCUP 2005
  2. bridging classifier
  3. category selection
  4. web query classification

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SIGIR06
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SIGIR06: The 29th Annual International SIGIR Conference
August 6 - 11, 2006
Washington, Seattle, USA

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

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  • (2022)Differential Query Semantic AnalysisProceedings of the Fifteenth ACM International Conference on Web Search and Data Mining10.1145/3488560.3498503(535-543)Online publication date: 11-Feb-2022
  • (2021)Characterizing search activities on stack overflowProceedings of the 29th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering10.1145/3468264.3468582(919-931)Online publication date: 20-Aug-2021
  • (2021)Context-aware Target Apps Selection and Recommendation for Enhancing Personal Mobile AssistantsACM Transactions on Information Systems10.1145/344767839:3(1-30)Online publication date: 5-May-2021
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  • (2020)Query Classification with Multi-objective Backoff OptimizationProceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3397271.3401320(1925-1928)Online publication date: 25-Jul-2020
  • (2020)Tempura: Query Analysis with Structural TemplatesProceedings of the 2020 CHI Conference on Human Factors in Computing Systems10.1145/3313831.3376451(1-12)Online publication date: 21-Apr-2020
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  • (2020)Sentiment Analysis10.1017/9781108639286Online publication date: 23-Sep-2020
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