Computer Engineering and Applications ›› 2020, Vol. 56 ›› Issue (13): 194-198.DOI: 10.3778/j.issn.1002-8331.1903-0184

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Expert Finding Method Using Baysian Network on Query Semantic Extension

ZHENG Wei, HOU Hongxu, BAN Zhijie   

  1. 1.College of Computer Science, Inner Mongolia University, Hohhot 010021, China
    2.College of Science, Hebei North University, Zhangjiakou, Hebei 075000, China
  • Online:2020-07-01 Published:2020-07-02



  1. 1.内蒙古大学 计算机学院,呼和浩特 010021
    2.河北北方学院 理学院,河北 张家口 075000


Expert finding is a research hotspot in the field of entity retrieval. Aiming at the shortcomings of the classical expert discovery model, such as the assumption of indexing term independence and the low retrieval performance, and an expert discovery method of Bayesian network with query semantic extension is proposed. The model adopts four-layer network structure, which can realize graphical probabilistic inference, and the semantic extension of query terms can be realized by word vector technology. Experimental results show that the new model is superior to the classical expert discovery model in terms of multiple evaluation indexes, indicating that the new model can effectively extend the semantics of query terms and improve the performance of expert retrieval.

Key words: expert finding method, Bayesian network, query term



关键词: 专家发现方法, 贝叶斯网络, 查询术语