Hefbib : hierarchical expert finding in heterogeneous bibliographic network
Luo, Hao
Loading…
Permalink
https://hdl.handle.net/2142/88227
Description
Title
Hefbib : hierarchical expert finding in heterogeneous bibliographic network
Author(s)
Luo, Hao
Issue Date
2015-07-22
Director of Research (if dissertation) or Advisor (if thesis)
Han, Jiawei
Department of Study
Computer Science
Discipline
Computer Science
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
M.S.
Degree Level
Thesis
Keyword(s)
Expert Finding
Heterogeneous Information Network
Abstract
Expert finding systems allow users to type simple text queries and retrieve names of individuals who possess the expertise described in the queries. Such applications are especially useful in real world: conference orga- nizers may search for reviewers, company recruiters may search for talented candidates, graduate students may search for advisers and researchers may search for collaborators, etc. In this study, we propose Hefbib, a hierarchical approach to expert finding in heterogeneous bibliographic network, to construct an expert hierarchy given a seed textual topic hierarchy as well as retrieve authoritative experts given a search query. Experiments on synthetic toy examples and real-world DBLP dataset show promising results.
Use this login method if you
don't
have an
@illinois.edu
email address.
(Oops, I do have one)
IDEALS migrated to a new platform on June 23, 2022. If you created
your account prior to this date, you will have to reset your password
using the forgot-password link below.
