Semantic representation of scientific literature: bringing claims, contributions and named entities onto the Linked Open Data cloud

摘要: Processing (NLP) for Rhetorical Entity (RE) detection; (ii) Named (NE) recognition based on the Linked Open Data (LOD) cloud; and (iii) automatic knowledge base construction both NEs REs using semantic web ontologies that interconnect entities in documents with machine-readable LOD cloud. Results. We present a complete workflow to transform scientific literature into base, W3C standards RDF RDFS. A text mining pipeline, implemented GATE framework, automatically extracts rhetorical of type Claims Contributions from full-text literature. These are further enriched named entities, represented as URIs linked open data cloud, by integrating DBpedia Spotlight tool our workflow. Text results stored through flexible export process provides dynamic mapping annotations vocabularies rules base. created gold standard corpus computer science conference proceedings journal articles, where Claim Contribution sentences manually annotated their respective types URIs. The performance RE detection phase is evaluated against this corpus, it achieves an average Fmeasure 0.73. demonstrate number queries show how generated can provide support numerous use cases managing Availability. All software presented paper available under source licenses at http://www.semanticsoftware.info/semantic-scientific-literature-peerj-20... [19]. Development releases individual components additionally GitHub page https://github.com/SemanticSoftwareLab [20]. URL https://peerj.com/articles/cs-37/ [21] DOI 10.7717/peerj-cs.37 [22] Copyright © 2015 Sateli Witte. Distributed Creative Commons CC-BY 4.0. History Submitted 4 August Accepted 13 November Published 9 December Acknowledgments This work was partially funded NSERC Discovery Grant. funders had no role study design, collection analysis, decision publish, or preparation manuscript. Attachment Size peerj-cs-37.pdf [23] 8.69 MB Semantics Masses Except otherwise noted, all original content site copyright its author licensed Attribution-Share Alike 2.5 Canada License. Source (retrieved 2016-07-30 23:58 ): http://www.semanticsoftware.info/biblio/semantic-representation-scientific-literature-peerj-compsci-2015 Links: [1] http://www.semanticsoftware.info/users/bahar [2] http://www.semanticsoftware.info/taxonomy/term/418 [3] http://www.semanticsoftware.info/taxonomy/term/391 [4] http://www.semanticsoftware.info/category/blog-tags/natural-language-processing [5] http://www.semanticsoftware.info/taxonomy/term/419 [6] http://www.semanticsoftware.info/taxonomy/term/390 [7] http://www.semanticsoftware.info/category/blog-tags/semantic-publishing [8] http://www.semanticsoftware.info/category/blog-tags/semantic-web [9] http://www.semanticsoftware.info/category/topic/semantic-web [10] http://www.semanticsoftware.info/category/topic/semantic-computing [11] http://www.semanticsoftware.info/category/topic/nlp [12] http://www.semanticsoftware.info/category/topic/text-mining [13] http://www.semanticsoftware.info/biblio/author/73 [14] http://www.semanticsoftware.info/biblio/author/1 [15] http://www.semanticsoftware.info/biblio/author/161 [16] http://www.semanticsoftware.info/biblio/keyword/16 [17] http://www.semanticsoftware.info/biblio/keyword/104 [18] http://www.semanticsoftware.info/biblio/keyword/2 [19] http://www.semanticsoftware.info/semantic-scientific-literature-peerj-2015-supplements [20] http://dx.doi.org/10.7717/peerj-cs.37 http://www.semanticsoftware.info/system/files/peerj-cs-37.pdf