An RDF Based Fuzzy Ontology Using Neural Tensor Networks

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

Abedini Farhad; KEYVANPOUR MOHAMMAD REZA; MENHAJ MOHAMMAD BAGHER

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: INTERNATIONAL JOURNAL OF INFORMATION AND COMMUNICATION TECHNOLOGY RESEARCH Year:2019 | Volume:11 | Issue:1 Page(s): 45-56

Download Full-Text

View:

111

Download:

Cites:

Information Journal Paper

Title

An RDF Based Fuzzy Ontology Using Neural Tensor Networks

Author(s)

Abedini Farhad | KEYVANPOUR MOHAMMAD REZA | MENHAJ MOHAMMAD BAGHER | Issue Writer Certificate

Keywords

Ontology

Fuzzy Ontology

Facts

Neural Tensor Network

RDF

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.

Cites

No record.

References

No record.

Cite

APA: Copy

Abedini, Farhad, KEYVANPOUR, MOHAMMAD REZA, & MENHAJ, MOHAMMAD BAGHER. (2019). An RDF Based Fuzzy Ontology Using Neural Tensor Networks. INTERNATIONAL JOURNAL OF INFORMATION AND COMMUNICATION TECHNOLOGY RESEARCH, 11(1), 45-56. SID. https://sid.ir/paper/764022/en

Vancouver: Copy

Abedini Farhad, KEYVANPOUR MOHAMMAD REZA, MENHAJ MOHAMMAD BAGHER. An RDF Based Fuzzy Ontology Using Neural Tensor Networks. INTERNATIONAL JOURNAL OF INFORMATION AND COMMUNICATION TECHNOLOGY RESEARCH[Internet]. 2019;11(1):45-56. Available from: https://sid.ir/paper/764022/en

IEEE: Copy

Farhad Abedini, MOHAMMAD REZA KEYVANPOUR, and MOHAMMAD BAGHER MENHAJ, “An RDF Based Fuzzy Ontology Using Neural Tensor Networks,” INTERNATIONAL JOURNAL OF INFORMATION AND COMMUNICATION TECHNOLOGY RESEARCH, vol. 11, no. 1, pp. 45–56, 2019, [Online]. Available: https://sid.ir/paper/764022/en

Related Journal Papers

No record.

Related Seminar Papers

No record.

Related Plans

No record.

Recommended Workshops