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Semantic Software Lab
Concordia University
Montréal, Canada

What's in this paper? Combining Rhetorical Entities with Linked Open Data for Semantic Literature Querying

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TitleWhat's in this paper? Combining Rhetorical Entities with Linked Open Data for Semantic Literature Querying
Publication TypeConference Paper
Year of Publication2015
Refereed DesignationRefereed
AuthorsSateli, B., and R. Witte
Conference NameSemantics, Analytics, Visualisation: Enhancing Scholarly Data (SAVE-SD 2015)
Date Published05/2015
Conference LocationFlorence, Italy
Type of WorkFull Paper
KeywordsLinked Open Data, natural language processing, RDF, Semantic Publishing, Semantic Web

Finding research literature pertaining to a task at hand is one of the essential tasks that scientists face on daily basis. Standard information retrieval techniques allow to quickly obtain a vast number of potentially relevant documents. Unfortunately, the search results then require significant effort for manual inspection, where we would rather select relevant publications based on more fine-grained, semantically rich queries involving a publication's contributions, methods, or application domains.
We argue that a novel combination of three distinct methods can significantly advance this vision: (i) Natural Language Processing (NLP) for Rhetorical Entity (RE) detection; (ii) Named Entity (NE) recognition based on the Linked Open Data (LOD) cloud; and (iii) automatic generation of RDF triples for both NEs and REs using semantic web ontologies to interconnect them. Combined in a single workflow, these techniques allow us to automatically construct a knowledge base that facilitates numerous advanced use cases for managing scientific documents.


Received "Best Paper Award" at SAVE-SD 2015


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