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A citation-based approach to automatic topical indexing of scientific literature

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Show simple item record Mahdi, Abdulhussain E. Joorabchi, Arash 2014-10-22T11:35:11Z 2014-10-22T11:35:11Z 2010
dc.description peer-reviewed en_US
dc.description.abstract Topical indexing of documents with keyphrases is a common method used for revealing the subject of scientific and research documents to both human readers and information retrieval tools, such as search engines. However, scientific documents that are manually indexed with keyphrases are still in the minority. This article describes a new unsupervised method for automatic keyphrase extraction from scientific documents which yields a performance on a par with human indexers. The method is based on identifying references cited in the document to be indexed and, using the keyphrases assigned to those references, for generating a set of high-likelihood keyphrases for the document. We have evaluated the performance of the proposed method by using it to automatically index a third-party testset of research documents. Reported experimental results show that the performance of our method, measured in terms of consistency with human indexers, is competitive with that achieved by state-of-the-art supervised methods. en_US
dc.language.iso eng en_US
dc.publisher Sage Publications en_US
dc.relation.ispartofseries Journal of Information Science;36, (6), pp. 798-811
dc.subject citation-based indexing en_US
dc.subject data mining en_US
dc.subject keyphrase extraction en_US
dc.subject topical indexing en_US
dc.subject extraction en_US
dc.title A citation-based approach to automatic topical indexing of scientific literature en_US
dc.type info:eu-repo/semantics/article
dc.type.supercollection all_ul_research en_US
dc.type.supercollection ul_published_reviewed en_US 2014-10-21T17:02:03Z
dc.description.version ACCEPTED
dc.rights.accessrights info:eu-repo/semantics/openAccess en_US
dc.internal.rssid 1130086
dc.internal.copyrightchecked Yes
dc.description.status peer-reviewed

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