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Authors: Paulo Figueiras 1 ; Ruben Costa 2 ; Luis Paiva 3 ; Celson Lima 4 and Ricardo Jardim-Gonçalves 2

Affiliations: 1 UNINOVA, Portugal ; 2 UNINOVA and Universidade Nova de Lisboa, Portugal ; 3 Universidade Nova de Lisboa, Portugal ; 4 Federal University of Western Pará, Brazil

ISBN: 978-989-8565-30-3

Keyword(s): Information Retrieval, Ontology Engineering, Knowledge Representation.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Data Engineering ; Enterprise Information Systems ; Information Systems Analysis and Specification ; Knowledge Engineering and Ontology Development ; Knowledge Representation ; Knowledge-Based Systems ; Ontologies and the Semantic Web ; Ontology Engineering ; Process Knowledge and Semantic Services ; Symbolic Systems

Abstract: This work introduces a conceptual framework and its current implementation to support the classification and discovery of knowledge sources, where every knowledge source is represented through a vector (named Semantic Vector - SV). The novelty of this work addresses the enrichment of such knowledge representations, using the classical vector space model concept extended with ontological support, which means to use ontological concepts and their relations to enrich each SV. Our approach takes into account three different but complementary processes using the following inputs: (1) the statistical relevance of keywords, (2) the ontological concepts, and (3) the ontological relations. SVs are compared against each other, in order to obtain their similarity index, and better support end users with a search/retrieval of knowledge sources capabilities. This paper presents the technical architecture (and respective implementation) supporting the conceptual framework, emphasizing the SV creati on process. Moreover, it provides some examples detailing the indexation process of knowledge sources, results achieved so far and future goals pursued here are also presented. (More)

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Paper citation in several formats:
Figueiras, P.; Costa, R.; Paiva, L.; Lima, C. and Jardim-Gonçalves, R. (2012). Information Retrieval in Collaborative Engineering Projects - A Vector Space Model Approach.In Proceedings of the International Conference on Knowledge Engineering and Ontology Development - Volume 1: KEOD, (IC3K 2012) ISBN 978-989-8565-30-3, pages 233-238. DOI: 10.5220/0004139302330238

@conference{keod12,
author={Paulo Figueiras. and Ruben Costa. and Luis Paiva. and Celson Lima. and Ricardo Jardim{-}Gon\c{C}alves.},
title={Information Retrieval in Collaborative Engineering Projects - A Vector Space Model Approach},
booktitle={Proceedings of the International Conference on Knowledge Engineering and Ontology Development - Volume 1: KEOD, (IC3K 2012)},
year={2012},
pages={233-238},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004139302330238},
isbn={978-989-8565-30-3},
}

TY - CONF

JO - Proceedings of the International Conference on Knowledge Engineering and Ontology Development - Volume 1: KEOD, (IC3K 2012)
TI - Information Retrieval in Collaborative Engineering Projects - A Vector Space Model Approach
SN - 978-989-8565-30-3
AU - Figueiras, P.
AU - Costa, R.
AU - Paiva, L.
AU - Lima, C.
AU - Jardim-Gonçalves, R.
PY - 2012
SP - 233
EP - 238
DO - 10.5220/0004139302330238

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