Explicit Graphical Relevance Feedback for Scholarly Information Retrieval
Lee, Shaoshing; Guo, Chun; Liu, Xiaozhong
Loading…
Permalink
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
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
Language
English
Permalink
http://hdl.handle.net/2142/73725
Copyright and License Information
Copyright 2015 is held by the authors. Copyright permissions, when appropriate, must be obtained directly from the authors.
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.