Using full-text citation network to enhance the keyword label performance

Pan, Youneng; Liu, Xiaozhong

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https://hdl.handle.net/2142/73719 Copy

Description

Title

Using full-text citation network to enhance the keyword label performance

Author(s)

• Pan, Youneng
• Liu, Xiaozhong

Issue Date

2015-03-15

Keyword(s)

• information seeking/retrieval
• natural language processing
• text/data/knowledge mining

Abstract

Keyword metadata is very important to the retrieval and management of scientific publications. However, keyword sparseness, in the scientific repository, threatens the usability, and manually assigning keywords is laborious and inefficiency. In this study, we investigate an automatic keyword assigning approach based on full-text citation analysis and supervised topic model, which can characterize the semantic relation between keyword label and the contextual meaning. Full-text citation network is constructed with publication topic distribution and citation topical motivation, which may potentially enhance the keyword label performance.

Publisher

iSchools

Series/Report Name or Number

iConference 2015 Proceedings

Type of Resource

text

Language

English

Permalink

http://hdl.handle.net/2142/73719

Copyright and License Information

Copyright 2015 is held by the authors. Copyright permissions, when appropriate, must be obtained directly from the authors.

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