poster

Constructing query-specific knowledge bases

Authors:

Jeffrey Dalton,

Laura DietzAuthors Info & Claims

AKBC '13: Proceedings of the 2013 workshop on Automated knowledge base construction

Pages 55 - 60

https://doi.org/10.1145/2509558.2509568

Published: 27 October 2013 Publication History

Abstract

Abstract Large general purpose knowledge bases (KB) support a variety of complex tasks because of their structured relationships. However, these KBs lack coverage for specialized topics or use cases. In these scenarios, users often use keyword search over large unstructured collections, such as the web. Instead, we propose constructing a 'knowledge sketch' that leverages existing KB data elements and relevant text documents to construct query-specific KB data. A knowledge sketch is a distribution over entities, documents, and relationships between entities, all for a specific information need. In our experiments we construct knowledge sketches for queries from the TREC 2004 Robust track, which emphasizes complex queries which perform poorly with existing text retrieval approaches.

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Cited By

El Zein DCâmara ADa Costa Pereira CTettamanzi A(2023)RULKNE: Representing User Knowledge State in Search-as-Learning with Named EntitiesProceedings of the 2023 Conference on Human Information Interaction and Retrieval10.1145/3576840.3578330(388-393)Online publication date: 19-Mar-2023
https://dl.acm.org/doi/10.1145/3576840.3578330

Index Terms

Constructing query-specific knowledge bases
1. Information systems
  1. Information retrieval
    1. Retrieval models and ranking

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Published In

cover image ACM Conferences

AKBC '13: Proceedings of the 2013 workshop on Automated knowledge base construction

October 2013

124 pages

ISBN:9781450324113

DOI:10.1145/2509558

Program Chairs:
Fabian M. Suchanek
Max Planck Institute for Informatics, Germany
,
Sebastian Riedel
University College London, UK
,
Sameer Singh
University of Massachusetts Amherst, USA
,
Partha Pratim Talukdar
Carnegie Mellon University, USA

Copyright © 2013 ACM.

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Publication History

Published: 27 October 2013

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CIKM'13

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CIKM'13: 22nd ACM International Conference on Information and Knowledge Management

October 27 - 28, 2013

California, San Francisco, USA

Acceptance Rates

AKBC '13 Paper Acceptance Rate 9 of 19 submissions, 47%;

Overall Acceptance Rate 9 of 19 submissions, 47%

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CIKM '25

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sigir
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The 34th ACM International Conference on Information and Knowledge Management

November 10 - 14, 2025

Seoul , Republic of Korea

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Cited By

El Zein DCâmara ADa Costa Pereira CTettamanzi A(2023)RULKNE: Representing User Knowledge State in Search-as-Learning with Named EntitiesProceedings of the 2023 Conference on Human Information Interaction and Retrieval10.1145/3576840.3578330(388-393)Online publication date: 19-Mar-2023
https://dl.acm.org/doi/10.1145/3576840.3578330

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