• DocumentCode
    2806456
  • Title

    Incorporating Similar People for Expert Finding in Enterprise Corpora

  • Author

    Zhang, Wei ; Ma, Jianqing ; Zhong, YiPing

  • Author_Institution
    Sch. of Inf. Sci. & Eng., Fudan Univ., Shanghai, China
  • fYear
    2009
  • fDate
    11-13 Dec. 2009
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    The task of finding authoritative people within an organization has received increased interest over the past few years. To identify an expert in a specific field, expertise evidence of candidates should be collected in the enterprise corpora to represent one\´s knowledge and skills. Though there have been various methods proposed for evidence collecting and expertise modeling, little work has been done to collect evidence by exploring the relationship between candidates. In this paper, we build a "bridge" between candidates to find out people who have similar intellectual structure within the organization and then supplement an individual by incorporating the evidence collected for his similar people. Besides, a document prior based on the PageRank weight is adopted to illustrate the significance of a page so as to improve the performance of the expert finding system. Finally, we evaluate our methods on enterprise corpora provided by TREC. Experimental results show that the incorporation of similar people and the document prior bring gains to the final results and our proposed methods have excellent performance.
  • Keywords
    document handling; organisational aspects; search engines; PageRank weight; TREC; authoritative people; document prior; enterprise corpora; evidence collecting; expert finding system; expertise modeling; intellectual structure; Bridges; Databases; Information analysis; Information science; Performance gain; Standards organizations;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Software Engineering, 2009. CiSE 2009. International Conference on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-4507-3
  • Electronic_ISBN
    978-1-4244-4507-3
  • Type

    conf

  • DOI
    10.1109/CISE.2009.5362743
  • Filename
    5362743