Can SKOS Ontologies Improve the Accuracy of Measuring Semantic Similarity of Purchase Orders?

Steven B. Kraines

2014

Abstract

The effect of additional domain knowledge provided by a SKOS ontology on the accuracy of semantic similarity calculated from product item lists in purchase orders for a manufacturer of modular building parts is examined. The accuracy of the calculated semantic similarities is evaluated against attribute information of the purchase orders, under the assumption that orders with similar attributes, such as the industrial type of the purchasing entities and the type of application of the modular building, will have similar lists of items. When all attributes of the purchase orders are weighted equally, the SKOS ontology does not appear to increase the accuracy of the calculated item list similarities. However, when only the two attributes that give the highest correlation to item list similarity values are used, the strongest correlation between item list similarity and entity attribute similarity is obtained when the SKOS-ontology is included in the calculation. Still, even the best correlation between item list and entity attribute similarities yields a correlation coefficient of less than 0.01. It is suggested that inclusion of semantic knowledge about the relationship between the set of items in the purchase orders, e.g. via the use of description logics, might increase the accuracy of the calculated semantic similarity values.

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Paper Citation


in Harvard Style

B. Kraines S. (2014). Can SKOS Ontologies Improve the Accuracy of Measuring Semantic Similarity of Purchase Orders? . In Proceedings of the International Conference on Knowledge Engineering and Ontology Development - Volume 1: KEOD, (IC3K 2014) ISBN 978-989-758-049-9, pages 248-255. DOI: 10.5220/0005074702480255


in Bibtex Style

@conference{keod14,
author={Steven B. Kraines},
title={Can SKOS Ontologies Improve the Accuracy of Measuring Semantic Similarity of Purchase Orders?},
booktitle={Proceedings of the International Conference on Knowledge Engineering and Ontology Development - Volume 1: KEOD, (IC3K 2014)},
year={2014},
pages={248-255},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005074702480255},
isbn={978-989-758-049-9},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Knowledge Engineering and Ontology Development - Volume 1: KEOD, (IC3K 2014)
TI - Can SKOS Ontologies Improve the Accuracy of Measuring Semantic Similarity of Purchase Orders?
SN - 978-989-758-049-9
AU - B. Kraines S.
PY - 2014
SP - 248
EP - 255
DO - 10.5220/0005074702480255