Bridging data mining and semantic web

Nowadays Semantic Web is widely adopted standard of knowledge representation. Hence, knowledge engineers are applying sophisticated methods to capture, discover and represent knowledge in Semantic Web form. Studies show that, to represent knowledge in Semantic Web standard, data mining techniques su...

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Main Author: Aman, Edris
Other Authors: Informaatioteknologian tiedekunta, Faculty of Information Technology, Tietotekniikan laitos, Department of Mathematical Information Technology, University of Jyväskylä, Jyväskylän yliopisto
Format: Master's thesis
Language:eng
Published: 2016
Subjects:
Online Access: https://jyx.jyu.fi/handle/123456789/52274
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author Aman, Edris
author2 Informaatioteknologian tiedekunta Faculty of Information Technology Tietotekniikan laitos Department of Mathematical Information Technology University of Jyväskylä Jyväskylän yliopisto
author_facet Aman, Edris Informaatioteknologian tiedekunta Faculty of Information Technology Tietotekniikan laitos Department of Mathematical Information Technology University of Jyväskylä Jyväskylän yliopisto Aman, Edris Informaatioteknologian tiedekunta Faculty of Information Technology Tietotekniikan laitos Department of Mathematical Information Technology University of Jyväskylä Jyväskylän yliopisto
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description Nowadays Semantic Web is widely adopted standard of knowledge representation. Hence, knowledge engineers are applying sophisticated methods to capture, discover and represent knowledge in Semantic Web form. Studies show that, to represent knowledge in Semantic Web standard, data mining techniques such as Decision Trees, Association Rules, etc., play an important role. These techniques are implemented in publicly available Data Mining tools. These tools represent knowledge discovered in human readable format and some tools use Predictive Model Markup language (PMML). PMML is an XML based model for data mining model representation that fails to address the representation of the semantics of the discovered knowledge. Hence, this thesis tries to research and give solutions to translate PMML to Semantic Web Rule Language (SWRL) format using Semantic Web technologies and data mining to cover the semantic gap in PMML.
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spellingShingle Aman, Edris Bridging data mining and semantic web Decision Tree Ontology Sematic web SWRL PMML Rule-based knowledge Tietotekniikka Mathematical Information Technology 602 ontologia semanttinen web
title Bridging data mining and semantic web
title_full Bridging data mining and semantic web
title_fullStr Bridging data mining and semantic web Bridging data mining and semantic web
title_full_unstemmed Bridging data mining and semantic web Bridging data mining and semantic web
title_short Bridging data mining and semantic web
title_sort bridging data mining and semantic web
title_txtP Bridging data mining and semantic web
topic Decision Tree Ontology Sematic web SWRL PMML Rule-based knowledge Tietotekniikka Mathematical Information Technology 602 ontologia semanttinen web
topic_facet 602 Decision Tree Mathematical Information Technology Ontology PMML Rule-based knowledge SWRL Sematic web Tietotekniikka ontologia semanttinen web
url https://jyx.jyu.fi/handle/123456789/52274 http://www.urn.fi/URN:NBN:fi:jyu-201612125050
work_keys_str_mv AT amanedris bridgingdataminingandsemanticweb