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Bayesian Belief Network Model Using Sematic Concept for Expert Finding

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Knowledge Science, Engineering and Management (KSEM 2021)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 12816))

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Abstract

The Expert finding is a research hotspot in the area of entity retrieval. However, due to the small number of search terms, the retrieval effect will be poor due to the mechanical text matching. In view of the above shortcomings, we use Bayesian belief network as a model frame, and two expert finding models are proposed. One is a basic semantic belief network retrieval model, in which BERT and LDA models are used, and the other is a compound semantic belief network model. The compound model uses an effective data fusion technique to integrate the retrieval results of the two sub-models in this paper. The paper presents the topology and retrieval algorithm of two models proposed. The experiments verify the validity of the research content on Amine platform. Experimental results show that the semantic model can improve the MAP value, and the compound semantic model is better than the existing expert finding model on multiple evaluation indicators such as P@N, MAP and MRR, and it can improve the performance of expert retrieval.

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Acknowledgment

This work is supported by the Natural Science Research Program of Hebei North University (YB2020003), Inner Mongolia Natural Science Foundation of China (2018MS06005) and Inner Mongolia autonomous region science and technology achievements transformation special (2019CG028).

Author information

Authors and Affiliations

  1. College of Compter Science, Inner Mongolia University, Hohhot, China

    Wei Zheng, Hongxu Hou, Nier Wu & Shuo Sun

  2. College of Science of Science, Hebei North University, Zhangjiakou, China

    Wei Zheng

Authors
  1. Wei Zheng
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  2. Hongxu Hou
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  3. Nier Wu
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  4. Shuo Sun
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Corresponding author

Correspondence to Hongxu Hou .

Editor information

Editors and Affiliations

  1. Tsinghua University, Beijing, China

    Han Qiu

  2. Ibaraki University, Hitachi, Japan

    Cheng Zhang

  3. University of Kentucky, Lexington, KY, USA

    Zongming Fei

  4. Texas A&M University – Commerce, Commerce, TX, USA

    Meikang Qiu

  5. Princeton University, Princeton, NJ, USA

    Sun-Yuan Kung

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Zheng, W., Hou, H., Wu, N., Sun, S. (2021). Bayesian Belief Network Model Using Sematic Concept for Expert Finding. In: Qiu, H., Zhang, C., Fei, Z., Qiu, M., Kung, SY. (eds) Knowledge Science, Engineering and Management . KSEM 2021. Lecture Notes in Computer Science(), vol 12816. Springer, Cham. https://doi.org/10.1007/978-3-030-82147-0_10

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  • DOI: https://doi.org/10.1007/978-3-030-82147-0_10

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-82146-3

  • Online ISBN: 978-3-030-82147-0

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