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CALCULATING SEMANTIC SIMILARITY BETWEEN COMPUTER-UNDERSTANDABLE DESCRIPTORS OF SCIENTIFIC RESEARCH

Topics: Communication, Collaboration and Information Sharing; Innovation Facilitation; Intelligent Information Systems; KM Strategies and Implementations ; Metadata and Structured Documents; Social Networks and the Psychological Dimension; Studies, Metrics & Benchmarks; Tools and Technology for Knowledge Management

Authors: Steven B. Kraines and Weisen Guo

Affiliation: University of Tokyo, Japan

Keyword(s): Knowledge Representation, Semantic Matching, Semantic Similarity, Logic Inference.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Communication, Collaboration and Information Sharing ; Innovation Facilitation ; Intelligent Information Systems ; KM Strategies and Implementations ; Knowledge Management and Information Sharing ; Knowledge-Based Systems ; Metadata and Structured Documents ; Social Networks and the Psychological Dimension ; Studies, Metrics & Benchmarks ; Symbolic Systems ; Tools and Technology for Knowledge Management

Abstract: If researchers created computer-understandable descriptors as part of the process of authoring journal articles and other expert knowledge resources, intelligent computer-aided matching and searching applications that are critical for addressing complex and large-scale problems in society could be realized. The EKOSS system enables knowledge experts to create computer-understandable descriptors of their knowledge resources using description logics ontologies as formal knowledge representation languages. The descriptors, called semantic statements, are authored as description logic ABoxes in reference to a shared domain ontology in the form of a TBox. Reasoners using logic-based inference can then measure the semantic similarity between semantic statements, which can be applied in knowledge searching, mining and integration applications. A method for semantic matching that uses logic inference based on a DL ontology TBox to increase both the precision and recall of matching descriptor s created as ABoxes is described, and the accuracy of the method compared to matching without logic inference is analyzed between a set of 15 semantic statements created using EKOSS to describe research articles related to sustainability science. (More)

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Paper citation in several formats:
B. Kraines, S. and Guo, W. (2011). CALCULATING SEMANTIC SIMILARITY BETWEEN COMPUTER-UNDERSTANDABLE DESCRIPTORS OF SCIENTIFIC RESEARCH. In Proceedings of the International Conference on Knowledge Management and Information Sharing (IC3K 2011) - KMIS; ISBN 978-989-8425-81-2; ISSN 2184-3228, SciTePress, pages 146-151. DOI: 10.5220/0003637001460151

@conference{kmis11,
author={Steven {B. Kraines}. and Weisen Guo.},
title={CALCULATING SEMANTIC SIMILARITY BETWEEN COMPUTER-UNDERSTANDABLE DESCRIPTORS OF SCIENTIFIC RESEARCH},
booktitle={Proceedings of the International Conference on Knowledge Management and Information Sharing (IC3K 2011) - KMIS},
year={2011},
pages={146-151},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003637001460151},
isbn={978-989-8425-81-2},
issn={2184-3228},
}

TY - CONF

JO - Proceedings of the International Conference on Knowledge Management and Information Sharing (IC3K 2011) - KMIS
TI - CALCULATING SEMANTIC SIMILARITY BETWEEN COMPUTER-UNDERSTANDABLE DESCRIPTORS OF SCIENTIFIC RESEARCH
SN - 978-989-8425-81-2
IS - 2184-3228
AU - B. Kraines, S.
AU - Guo, W.
PY - 2011
SP - 146
EP - 151
DO - 10.5220/0003637001460151
PB - SciTePress