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Extracting Semantic Concept Relations from Wikipedia

Published: 02 June 2014 Publication History

Abstract

Background knowledge as provided by repositories such as WordNet is of critical importance for linking or mapping ontologies and related tasks. Since current repositories are quite limited in their scope and currentness, we investigate how to automatically build up improved repositories by extracting semantic relations (e.g., is-a and part-of relations) from Wikipedia articles. Our approach uses a comprehensive set of semantic patterns, finite state machines and NLP-techniques to process Wikipedia definitions and to identify semantic relations between concepts. Our approach is able to extract multiple relations from a single Wikipedia article. An evaluation for different domains shows the high quality and effectiveness of the proposed approach.

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    cover image ACM Other conferences
    WIMS '14: Proceedings of the 4th International Conference on Web Intelligence, Mining and Semantics (WIMS14)
    June 2014
    506 pages
    ISBN:9781450325387
    DOI:10.1145/2611040
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Published: 02 June 2014

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    Author Tags

    1. Information extraction
    2. background knowledge
    3. natural language processing
    4. semantic relations
    5. thesauri
    6. wikipedia

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    WIMS '14 Paper Acceptance Rate 41 of 90 submissions, 46%;
    Overall Acceptance Rate 140 of 278 submissions, 50%

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    • (2022)Arabic Knowledge Graph Construction: A close look in the present and into the futureJournal of King Saud University - Computer and Information Sciences10.1016/j.jksuci.2022.04.00734:9(6505-6523)Online publication date: Oct-2022
    • (2021)Recent trends in knowledge graphs: theory and practiceSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-021-05756-825:13(8337-8355)Online publication date: 1-Jul-2021
    • (2021)Extracting Semantic Concepts and Relations from Scientific Publications by Using Deep LearningInnovative Systems for Intelligent Health Informatics10.1007/978-3-030-70713-2_35(374-383)Online publication date: 6-May-2021
    • (2019)A bilingual ontology mapping and enrichment approach for domain ontologies in e-learningProceedings of the 20th International Conference on Computer Systems and Technologies10.1145/3345252.3345257(284-291)Online publication date: 21-Jun-2019
    • (2019)A Combined Approach for Eliciting Relationships for Educational Ontologies Using General-Purpose Knowledge BasesIEEE Access10.1109/ACCESS.2019.29100797(48339-48355)Online publication date: 2019
    • (2018)Cross-lingual and multilingual ontology mapping - surveyProceedings of the 19th International Conference on Computer Systems and Technologies10.1145/3274005.3274034(50-57)Online publication date: 13-Sep-2018
    • (2018)Construction of Encyclopedic Knowledge Base from Infobox of Indonesian Wikipedia2018 International Conference on Information Technology Systems and Innovation (ICITSI)10.1109/ICITSI.2018.8695937(542-546)Online publication date: Oct-2018
    • (2018)Hypernym-Hyponym Relation Extraction from Indonesian Wikipedia Text2018 International Conference on Asian Language Processing (IALP)10.1109/IALP.2018.8629216(285-289)Online publication date: Nov-2018
    • (2018)Towards Semantic Interoperability for IoT: Combining Social Tagging Data and Wikipedia to Generate a Domain-Specific OntologyRecent Trends in Data Science and Soft Computing10.1007/978-3-319-99007-1_34(355-363)Online publication date: 9-Sep-2018
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