%0 Conference Proceedings
%T Rule Based Combined Tagger for Marathi Text
%+ Babasaheb Bhimrao Ambedkar Bihar University
%A Khandale, Kalpana, B.
%A Namrata Mahender, C.
%Z Part 1: Machine Learning (ML), Deep Learning (DL), Internet of Things (IoT)
%< avec comité de lecture
%( IFIP Advances in Information and Communication Technology
%B 4th International Conference on Computational Intelligence in Data Science (ICCIDS)
%C Chennai, India
%Y Vallidevi Krishnamurthy
%Y Suresh Jaganathan
%Y Kanchana Rajaram
%Y Saraswathi Shunmuganathan
%I Springer International Publishing
%3 Computational Intelligence in Data Science
%V AICT-611
%P 90-101
%8 2021-03-18
%D 2021
%R 10.1007/978-3-030-92600-7_9
%K Annotated corpus
%K Unigram
%K Bigram
%K POS tagging
%Z Computer Science [cs]Conference papers
%X Part of speech (POS) tagging is most necessary concept in the natural language processing categorized each word in the corpus. This paper focus on the development of Marathi part of speech tagger using the N-gram models. For this we have designed rules for the development of the POS tagger. These rules are framed on the basis of the Marathi grammar. The corpus is of 635 Marathi sentences written in considering variations, for better evaluation of the POS tagger. Total 5715 words has been tagged from in which 1918 words unigram tagger and 106 words are tagged by the bigram tagger. The overall accuracy of POS tagger is 79.34%.
%G English
%Z TC 12
%2 https://inria.hal.science/hal-03772943/document
%2 https://inria.hal.science/hal-03772943/file/512058_1_En_9_Chapter.pdf
%L hal-03772943
%U https://inria.hal.science/hal-03772943
%~ IFIP-LNCS
%~ IFIP
%~ IFIP-AICT
%~ IFIP-TC
%~ IFIP-TC12
%~ IFIP-ICCIDS
%~ IFIP-AICT-611