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Author: Jörg Brunsmann

Affiliation: Faculty of Mathematics and Computer Science and Distance University of Hagen, Germany

ISBN: 978-989-8425-29-4

Keyword(s): Semantic Web, Social Search, Semantic Search, Natural Language Processing, Ontology Matching, Onotoloy Alignment, Linked Data, Provenance, Digital Archives, Knowledge Management, Resource Description Framework, Ontologies.

Related Ontology Subjects/Areas/Topics: Applications ; Artificial Intelligence ; Collaboration and e-Services ; Data Engineering ; e-Business ; Enterprise Information Systems ; Human-Machine Cooperation ; Information Systems Analysis and Specification ; Knowledge Acquisition ; Knowledge Engineering and Ontology Development ; Knowledge Representation ; Knowledge-Based Systems ; Natural Language Processing ; Networked Ontologies ; Ontologies and the Semantic Web ; Ontology Engineering ; Ontology Matching and Alignment ; Pattern Recognition ; Semantic Web ; Soft Computing ; Symbolic Systems

Abstract: Private and business related knowledge acquisition is either performed via learning by doing or via human dialogue that includes transmission of social or collaborative questions and answers. Unfortunately it can be a time consuming task to find a trusted friend on the web for private recommendations or to find a qualified expert colleague in a (virtual) organisation for work-related questions or to find a suitable company contact person as a customer. Recently, such social question and answering is conducted with internet based technologies like social search engines which route a question to a appropriate human selected from a social or expert network. However, even if social search engines are involved, it is unlikely that existing social search approaches exploit machine-readable lightweight ontologies that enable classifying, publishing and sharing questions and answers to support subsequent semantic search without human involvement. This paper proposes the combination of semanti c web and social search technologies in order to publish and archive social and collaborative generated knowledge for future reuse. Since knowledge classifying vocabularies evolve over time the paper also describes why archived knowledge may become obsolete and how ontology matching methods are used to migrate knowledge to conform to contemporary vocabularies. (More)

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Paper citation in several formats:
Brunsmann, J. (2010). THE DESIGN OF A SOCIAL SEMANTIC SEARCH ENGINE - Preserving Archived Collaborative Engineering Knowledge with Ontology Matching .In Proceedings of the International Conference on Knowledge Engineering and Ontology Development - Volume 1: KEOD, (IC3K 2010) ISBN 978-989-8425-29-4, pages 200-205. DOI: 10.5220/0003070402000205

@conference{keod10,
author={Jörg Brunsmann.},
title={THE DESIGN OF A SOCIAL SEMANTIC SEARCH ENGINE - Preserving Archived Collaborative Engineering Knowledge with Ontology Matching },
booktitle={Proceedings of the International Conference on Knowledge Engineering and Ontology Development - Volume 1: KEOD, (IC3K 2010)},
year={2010},
pages={200-205},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003070402000205},
isbn={978-989-8425-29-4},
}

TY - CONF

JO - Proceedings of the International Conference on Knowledge Engineering and Ontology Development - Volume 1: KEOD, (IC3K 2010)
TI - THE DESIGN OF A SOCIAL SEMANTIC SEARCH ENGINE - Preserving Archived Collaborative Engineering Knowledge with Ontology Matching
SN - 978-989-8425-29-4
AU - Brunsmann, J.
PY - 2010
SP - 200
EP - 205
DO - 10.5220/0003070402000205

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