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Title:Using full-text citation network to enhance the keyword label performance
Author(s):Pan, Youneng; Liu, Xiaozhong
Subject(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.
Issue Date:2015-03-15
Series/Report:iConference 2015 Proceedings
Genre:Conference Poster
Peer Reviewed:yes
Rights Information:Copyright 2015 is held by the authors. Copyright permissions, when appropriate, must be obtained directly from the authors.
Date Available in IDEALS:2015-03-24

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