University of Illinois Urbana-Champaign

Explicit Graphical Relevance Feedback for Scholarly Information Retrieval

Lee, Shaoshing; Guo, Chun; Liu, Xiaozhong

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https://hdl.handle.net/2142/73725

Description

Title
Explicit Graphical Relevance Feedback for Scholarly Information Retrieval
Author(s)
  • Lee, Shaoshing
  • Guo, Chun
  • Liu, Xiaozhong
Issue Date
2015-03-15
Keyword(s)
  • information seeking/retrieval
  • human-computer interaction
  • text/data/knowledge mining
Date of Ingest
2015-03-24T16:07:38Z
Abstract
In this paper, we present a new method to collect users’ feedback on scientific heterogeneous graph to enhance the scientific information retrieval performance. Meanwhile, a new search system is implemented to validate the new feedback hypothesis. Unlike earlier approaches, by using the new search system scholars can mark the useful/not useful venues, papers, authors, and keywords on a heterogeneous graph, and the feedback algorithm can select the optimized paths on the graph to enhance the retrieval performance.
Publisher
iSchools
Series/Report Name or Number
iConference 2015 Proceedings
Type of Resource
text
Genre of Resource
Conference Poster
Language
English
Permalink
http://hdl.handle.net/2142/73725
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Copyright 2015 is held by the authors. Copyright permissions, when appropriate, must be obtained directly from the authors.

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