Mining the Web for Learning Ontologies: State of Art and Critical Review
International Journal of Sensors and Sensor Networks
Volume 5, Issue 5-1, September 2017, Pages: 13-17
Received: Mar. 30, 2017; Accepted: Apr. 7, 2017; Published: May 13, 2017
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Authors
Mohamed El Asikri, Department Mathematics and Informatics and Management, Laboratory of Engineering Sciences and Energy, Polydisciplinary Faculty of Ouarzazate, Ibn Zohr University, Agadir, Morocco
Salahddine Krit, Department Mathematics and Informatics and Management, Laboratory of Engineering Sciences and Energy, Polydisciplinary Faculty of Ouarzazate, Ibn Zohr University, Agadir, Morocco
Hassan Chaib, Department Mathematics and Informatics and Management, Laboratory of Engineering Sciences and Energy, Polydisciplinary Faculty of Ouarzazate, Ibn Zohr University, Agadir, Morocco
Mustapha Kabrane, Department Mathematics and Informatics and Management, Laboratory of Engineering Sciences and Energy, Polydisciplinary Faculty of Ouarzazate, Ibn Zohr University, Agadir, Morocco
Hassan Ouadani, Department Mathematics and Informatics and Management, Laboratory of Engineering Sciences and Energy, Polydisciplinary Faculty of Ouarzazate, Ibn Zohr University, Agadir, Morocco
Khaoula Karimi, Department Mathematics and Informatics and Management, Laboratory of Engineering Sciences and Energy, Polydisciplinary Faculty of Ouarzazate, Ibn Zohr University, Agadir, Morocco
Kaouthar Bendaouad, Department Mathematics and Informatics and Management, Laboratory of Engineering Sciences and Energy, Polydisciplinary Faculty of Ouarzazate, Ibn Zohr University, Agadir, Morocco
Hicham Elbousty, Department Mathematics and Informatics and Management, Laboratory of Engineering Sciences and Energy, Polydisciplinary Faculty of Ouarzazate, Ibn Zohr University, Agadir, Morocco
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Abstract
The aim of the paper is to investigate and present the subject of building ontologies using the Semantic Web Mining that is defined as the combination of the two fast-developing research areas Semantic Web and Web Mining.Web mining is the application of data mining techniques to the content, structure, and usage of Web resources and The Semantic Web is the second-generation WWW, enriched by machine-processable information which supports the user in his tasks.. This can help to discover global as well as local structure “models” or “patterns”within and between Web pages and ontology extraction witch is the automatic or semi-automatic creation of ontologies, including extracting the corresponding domain's terms and the relationships between those concepts, and encoding them with an ontology language for easy retrieval. As building ontologies manually is extremely labor-intensive and time-consuming, there is great motivation to automate the process. This paper gives an overview of where the two areas meet today, and discuss ways of how a closer integration could be profitable.
Keywords
Semantic Web, Web Mining, Ontology, Konwledge Discovery, Ontology Learning
To cite this article
Mohamed El Asikri, Salahddine Krit, Hassan Chaib, Mustapha Kabrane, Hassan Ouadani, Khaoula Karimi, Kaouthar Bendaouad, Hicham Elbousty, Mining the Web for Learning Ontologies: State of Art and Critical Review, International Journal of Sensors and Sensor Networks. Special Issue:Smart Cities Using a Wireless Sensor Networks. Vol. 5, No. 5-1, 2017, pp. 13-17. doi: 10.11648/j.ijssn.s.2017050501.13
Copyright
Copyright © 2017 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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