Development of a Hindi named entity recognition system without using manually annotated training corpus
Joint Authors
Source
The International Arab Journal of Information Technology
Issue
Vol. 15, Issue 6 (30 Nov. 2018)10 p.
Publisher
Publication Date
2018-11-30
Country of Publication
Jordan
No. of Pages
10
Main Subjects
Information Technology and Computer Science
Abstract EN
Machine learning based approach for named entity recognition (NER) requires sufficient annotated corpus to train the classifier.
Other NER resources like gazetteers are also required to make the classifier more accurate.
But in many languages and domains relevant NER resources are still not available.
Creation of adequate and relevant resources is costly and time consuming.
However a large amount of resources and several NER systems are available in resource-rich languages, like English.
Suitable language adaptation techniques, NER resources of a resource-rich language and minimally supervised learning might help to overcome such scenarios.
In this paper we have studied a few such techniques in order to develop a Hindi NER system.
Without using any Hindi NE annotated corpus we have achieved a reasonable accuracy of F-Measure 73.87 in the developed system
American Psychological Association (APA)
Saha, Sujan& Majumder, Mukta. 2018. Development of a Hindi named entity recognition system without using manually annotated training corpus. The International Arab Journal of Information Technology،Vol. 15, no. 6.
https://search.emarefa.net/detail/BIM-874018
Modern Language Association (MLA)
Saha, Sujan& Majumder, Mukta. Development of a Hindi named entity recognition system without using manually annotated training corpus. The International Arab Journal of Information Technology Vol. 15, no. 6 (Nov. 2018).
https://search.emarefa.net/detail/BIM-874018
American Medical Association (AMA)
Saha, Sujan& Majumder, Mukta. Development of a Hindi named entity recognition system without using manually annotated training corpus. The International Arab Journal of Information Technology. 2018. Vol. 15, no. 6.
https://search.emarefa.net/detail/BIM-874018
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-874018