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User-centric query refinement and processing using granularity-based strategies

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Abstract

Under the context of large-scale scientific literatures, this paper provides a user-centric approach for refining and processing incomplete or vague query based on cognitive- and granularity-based strategies. From the viewpoints of user interests retention and granular information processing, we examine various strategies for user-centric unification of search and reasoning. Inspired by the basic level for human problem-solving in cognitive science, we refine a query based on retained user interests. We bring the multi-level, multi-perspective strategies from human problem-solving to large-scale search and reasoning. The power/exponential law-based interests retention modeling, network statistics–based data selection, and ontology-supervised hierarchical reasoning are developed to implement these strategies. As an illustration, we investigate some case studies based on a large-scale scientific literature dataset, DBLP. The experimental results show that the proposed strategies are potentially effective.

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Authors and Affiliations

  1. International WIC Institute, Beijing University of Technology, 100124, Beijing, China

    Yi Zeng, Ning Zhong, Yan Wang, Yulin Qin, Haiyan Zhou & Yiyu Yao

  2. Department of Life Science and Informatics, Maebashi Institute of Technology, Maebashi, 371-0816, Japan

    Ning Zhong

  3. Department of Psychology, Carnegie Mellon University, Pittsburgh, PA, 15213, USA

    Yulin Qin

  4. Department of Computer Science, Vrije Universiteit Amsterdam, 1081 HV, Amsterdam, The Netherlands

    Zhisheng Huang & Frank van Harmelen

  5. Department of Computer Science, University of Regina, Regina, SK, S4S 0A2, Canada

    Yiyu Yao

Authors
  1. Yi Zeng
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  2. Ning Zhong
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  3. Yan Wang
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  4. Yulin Qin
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  5. Zhisheng Huang
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  6. Haiyan Zhou
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  7. Yiyu Yao
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  8. Frank van Harmelen
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Corresponding author

Correspondence to Ning Zhong.

Additional information

This study is partially supported by the European Commission through the Large-Scale Integrating Project LarKC (Large Knowledge Collider, FP7-215535) under the 7th framework programme.

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Zeng, Y., Zhong, N., Wang, Y. et al. User-centric query refinement and processing using granularity-based strategies. Knowl Inf Syst 27, 419–450 (2011). https://doi.org/10.1007/s10115-010-0298-8

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  • DOI: https://doi.org/10.1007/s10115-010-0298-8

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