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Title

An RDF Based Fuzzy Ontology Using Neural Tensor Networks

Year: 1397
COI: JR_ITRC-11-1_006
Language: EnglishView: 74
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Authors

Farhad Abedini - Faculty of Computer and Information Technology Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran
Mohammad Reza Keyvanpour - Department of Computer Engineering, Alzahra University, Vanak, Tehran, Iran
Mohammad Bagher Menhaj - lectrical Engineering Department, Amirkabir University of Technology, Hafez Ave., Tehran, Iran

Abstract:

As an extension of classical ontology, a fuzzy ontology by employing fuzzy set theory can easily and yet better deal with uncertainties especially for the cases in which knowledge is vague. Obviously, fuzzification plays an important role in each fuzzy ontology. The main goal of this paper is to present an RDF based ontology, which indeed should contain many facts about the real world, inevitably facing with some uncertainties. In this perspective, an RDF based ontology is converted into a fuzzy most probably an incomplete one due to the fact that there will be some missing relations in the converted fuzzy ontology. To remedy this, the paper introduces a new method in the general framework of conversion and completion of an RDF based ontology into a fuzzy ontology mainly using the facts aspect. Therefore, first a new definition of the fuzzy ontology is proposed. To do so, a neural tensor network, which is indeed state-of-the-art of RDF based ontology completion, is proposed. Furthermore, a new application is suggested for this network that can create a fuzzy ontology. To furnish this goal, two new algorithms are then introduced for the conversion and completion of the proposed fuzzy ontology. In the proposed method, ontology facts are first embedded in a vector space, and then a score value is given to each fact by a learning method. Using these scores and threshold values of each relation, ontology facts can be fuzzified. Finally, some simulation studies are conducted to evaluate better the merit of the proposed method.

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Paper COI Code

This Paper COI Code is JR_ITRC-11-1_006. Also You can use the following address to link to this article. This link is permanent and is used as an article registration confirmation in the Civilica reference:

https://civilica.com/doc/1152197/

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Abedini, Farhad and Keyvanpour, Mohammad Reza and Menhaj, Mohammad Bagher,1397,An RDF Based Fuzzy Ontology Using Neural Tensor Networks ,https://civilica.com/doc/1152197

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Scientometrics

The specifications of the publisher center of this Paper are as follows:
Type of center: Azad University
Paper count: 10,397
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