research-article

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

Authors:

Bahar Sateli and

René WitteAuthors Info & Claims

WWW '15 Companion: Proceedings of the 24th International Conference on World Wide Web

May 2015

Pages 1023 - 1028

https://doi.org/10.1145/2740908.2742022

Published: 18 May 2015 Publication History

Abstract

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.

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Cited By

Chen HNguyen HAlghamdi A(2022)Constructing a high-quality dataset for automated creation of summaries of fundamental contributions of research articlesScientometrics10.1007/s11192-022-04380-z127:12(7061-7075)Online publication date: 28-Apr-2022
https://doi.org/10.1007/s11192-022-04380-z
Constantopoulos PPertsas V(2020)From Publications to Knowledge GraphsInformation Search, Integration, and Personalization10.1007/978-3-030-44900-1_2(18-33)Online publication date: 27-Mar-2020
https://doi.org/10.1007/978-3-030-44900-1_2
Mesbah SLofi CTorre MBozzon AHouben G(2018)TSE-NER: An Iterative Approach for Long-Tail Entity Extraction in Scientific PublicationsThe Semantic Web – ISWC 201810.1007/978-3-030-00671-6_8(127-143)Online publication date: 18-Sep-2018
https://doi.org/10.1007/978-3-030-00671-6_8
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What's in this paper?: Combining Rhetorical Entities with Linked Open Data for Semantic Literature Querying

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cover image ACM Other conferences

WWW '15 Companion: Proceedings of the 24th International Conference on World Wide Web

May 2015

1602 pages

ISBN:9781450334730

DOI:10.1145/2740908

General Chairs:
Aldo Gangemi
National Research Council, Italy & Paris 13 University-CNRS, France
,
Stefano Leonardi
Sapienza University of Rome, Italy
,
Alessandro Panconesi
Sapienza University of Rome, Italy

Copyright © 2015 Copyright is held by the International World Wide Web Conference Committee (IW3C2).

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IW3C2: International World Wide Web Conference Committee

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SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 18 May 2015

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WWW '15

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WWW '15: 24th International World Wide Web Conference

May 18 - 22, 2015

Florence, Italy

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Overall Acceptance Rate 1,899 of 8,196 submissions, 23%

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Cited By

Chen HNguyen HAlghamdi A(2022)Constructing a high-quality dataset for automated creation of summaries of fundamental contributions of research articlesScientometrics10.1007/s11192-022-04380-z127:12(7061-7075)Online publication date: 28-Apr-2022
https://doi.org/10.1007/s11192-022-04380-z
Constantopoulos PPertsas V(2020)From Publications to Knowledge GraphsInformation Search, Integration, and Personalization10.1007/978-3-030-44900-1_2(18-33)Online publication date: 27-Mar-2020
https://doi.org/10.1007/978-3-030-44900-1_2
Mesbah SLofi CTorre MBozzon AHouben G(2018)TSE-NER: An Iterative Approach for Long-Tail Entity Extraction in Scientific PublicationsThe Semantic Web – ISWC 201810.1007/978-3-030-00671-6_8(127-143)Online publication date: 18-Sep-2018
https://doi.org/10.1007/978-3-030-00671-6_8
Pertsas VConstantopoulos PAndroutsopoulos I(2018)Ontology Driven Extraction of Research ProcessesThe Semantic Web – ISWC 201810.1007/978-3-030-00671-6_10(162-178)Online publication date: 8-Oct-2018
https://dl.acm.org/doi/10.1007/978-3-030-00671-6_10
Mesbah SFragkeskos KLofi CBozzon AHouben G(2017)Semantic Annotation of Data Processing Pipelines in Scientific PublicationsThe Semantic Web10.1007/978-3-319-58068-5_20(321-336)Online publication date: 16-May-2017
https://doi.org/10.1007/978-3-319-58068-5_20
Ronzano FSaggion H(2017)Knowledge Extraction and Modeling from Scientific PublicationsSemantics, Analytics, Visualization. Enhancing Scholarly Data10.1007/978-3-319-53637-8_2(11-25)Online publication date: 10-May-2017
https://doi.org/10.1007/978-3-319-53637-8_2
de Ribaupierre HOsborne FMotta EBourdeau JHendler JNkambou RHorrocks IZhao B(2016)Combining NLP And Semantics For Mining Software Technologies From Research PublicationsProceedings of the 25th International Conference Companion on World Wide Web10.1145/2872518.2889358(23-24)Online publication date: 11-Apr-2016
https://dl.acm.org/doi/10.1145/2872518.2889358
Gábor KZargayouna HTellier IBuscaldi DCharnois T(2016)Unsupervised Relation Extraction in Specialized Corpora Using Sequence MiningAdvances in Intelligent Data Analysis XV10.1007/978-3-319-46349-0_21(237-248)Online publication date: 21-Sep-2016
https://doi.org/10.1007/978-3-319-46349-0_21
Sateli BWitte R(2016)Automatic Construction of a Semantic Knowledge Base from CEUR Workshop ProceedingsSemantic Web Evaluation Challenges10.1007/978-3-319-25518-7_11(129-141)Online publication date: 7-Jan-2016
https://doi.org/10.1007/978-3-319-25518-7_11

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