Abstract
NER which is known as Named Entity Recognition is an application of Natural Language Processing (NLP). NER is an activity of Information Extraction. NER is a task used for automated text processing for various industries, a key concept for academics, artificial intelligence, robotics, Bioinformatics and much more. NER is always an essential activity when dealing with chief NLP activity such as machine translation, question-answering, document summarization etc. Most NER work has been done for other European languages. NER work has been done in few Indian constitutional languages. Not enough work is possible due to some challenges such as lack of resources, ambiguity in language, morphologically rich and much more. In this paper, to identify various named entities from a text document, rules are defined using Rule-based approach. Based on defined rules, three different test cases computed on the training dataset and achieved 70% of accuracy.
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Shah, D.N., Bhadka, H.B. (2018). Named Entity Recognition from Gujarati Text Using Rule-Based Approach. In: Abraham, A., Muhuri, P., Muda, A., Gandhi, N. (eds) Intelligent Systems Design and Applications. ISDA 2017. Advances in Intelligent Systems and Computing, vol 736. Springer, Cham. https://doi.org/10.1007/978-3-319-76348-4_76
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