Named Entities Recognition and Classification System for Persian Texts Based on Neural Network

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.

Zali Mojtaba; Firoozbakht Mohsen

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

Journal Paper

Paper Information

Journal: Iranian Journal of Information Processing & Management Year:2018 | Volume:34 | Issue:1 Page(s): 473-486

Download Full-Text

Persian Verion

View:

545

Download:

Cites:

Information Journal Paper

Title

Named Entities Recognition and Classification System for Persian Texts Based on Neural Network

Author(s)

Zali Mojtaba | Firoozbakht Mohsen | Issue Writer Certificate

Keywords

Natural Language ProcessingQ1

Named Entity RecognitionQ1

Neural NetworkQ2

Vector Representation of WordsQ1

Abstract

Named Entity Recognition (NER) is a fundamental task in Natural Language Processing and also known as a subset of information extraction. We seek to locate and classify named entities in text into predefined categories such as the names of persons, organizations, locations, expressions of times, etc. Named Entity Recognition for English texts has been researched widely for the past years, however only a few limited researches have emphasized on Persian NER due to absence of resources for Persian named entities and the limited amount of progress made in Persian Natural Language Processing in general. In this paper, a Persian Named Entity Recognition system has been developed based on Neural Network with the study of researches conducted in other languages and benefiting from the latest methods in this area such as using the Vector Representation of Words. The results from the proposed model show that word embedding features in Persian not only resolve the problem of feature selection, but also it could lead to the development of an efficient system with the least dependence to the domain.

Cites

No record.

References

No record.

Cite

APA: Copy

Zali, Mojtaba, & Firoozbakht, Mohsen. (2018). Named Entities Recognition and Classification System for Persian Texts Based on Neural Network. IRANIAN JOURNAL OF INFORMATION PROCESSING & MANAGEMENT (INFORMATION SCIENCES AND TECHNOLOGY), 34(1 ), 473-486. SID. https://sid.ir/paper/381728/en

Vancouver: Copy

Zali Mojtaba, Firoozbakht Mohsen. Named Entities Recognition and Classification System for Persian Texts Based on Neural Network. IRANIAN JOURNAL OF INFORMATION PROCESSING & MANAGEMENT (INFORMATION SCIENCES AND TECHNOLOGY)[Internet]. 2018;34(1 ):473-486. Available from: https://sid.ir/paper/381728/en

IEEE: Copy

Mojtaba Zali, and Mohsen Firoozbakht, “Named Entities Recognition and Classification System for Persian Texts Based on Neural Network,” IRANIAN JOURNAL OF INFORMATION PROCESSING & MANAGEMENT (INFORMATION SCIENCES AND TECHNOLOGY), vol. 34, no. 1 , pp. 473–486, 2018, [Online]. Available: https://sid.ir/paper/381728/en

Related Journal Papers