Quotation Fernandez, Miriam, Sabou, Reka Marta, Knoth, Petr, Motta, Enrico. 2010. Predicting the quality of semantic relations by applying Machine Learning classi ers. European Knowledge Acquisition Workshop (EKAW), 2010, Lisbon, Portugal, 11.20.-15.10.


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Abstract

In this paper, we propose the application of Machine Learning (ML) methods to the Semantic Web (SW) as a mechanism to pre- dict the correctness of semantic relations. For this purpose, we have acquired a learning dataset from the SW and we have per- formed an extensive experimental evaluation covering more than 1,800 relations of various types. We have obtained encouraging results, reaching a maximum of 74.2% of correctly classified se- mantic relations for classifiers able to validate the correctness of multiple types of semantic relations (generic classifiers) and up to 98% for classifiers focused on evaluating the correctness of one particular semantic relation (specialized classifiers)

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Publication's profile

Status of publication Published
Affiliation External
Type of publication Poster presented at an academic conference or symposium
Language English
Title Predicting the quality of semantic relations by applying Machine Learning classi ers
Event European Knowledge Acquisition Workshop (EKAW), 2010
Date 11.20.-15.10.
Location Lisbon
Country Portugal
Year 2010
URL http://ceur-ws.org/Vol-674/Paper92.pdf

Associations

People
Sabou, Reka Marta (Details)
External
Fernandez, Miriam (The Open University, United Kingdom)
Knoth, Petr (The Open University, United Kingdom)
Motta, Enrico (The Open University, United Kingdom)
Organization
Institute for Data, Process and Knowledge Management (AE Sabou) (Details)
Research areas (Ă–STAT Classification 'Statistik Austria')
1109 Information and data processing (Details)
1122 Artificial intelligence (Details)
1127 Information science (Details)
1138 Information systems (Details)
1140 Software engineering (Details)
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