Part-of-speech tagger for Konkani-English code-mixed social media text

dc.contributor.author	Phadte, A.
dc.contributor.author	Arsekar, R.
dc.date.accessioned	2018-05-31T10:37:53Z
dc.date.available	2018-05-31T10:37:53Z
dc.date.issued	2018
dc.identifier.citation	Natural Language Processing and Information Systems, Ed. by: Silberztein M., Atigui F., Kornyshova E., M'tais E., Meziane F. NLDB 2018. Lecture Notes in Computer Science. Springer, Cham. 10859; 2018; 303-307.	en_US
dc.identifier.uri	https://doi.org/10.1007/978-3-319-91947-8_31
dc.identifier.uri	http://irgu.unigoa.ac.in/drs/handle/unigoa/5231
dc.description.abstract	An efficient and less resource-intensive strategies for Konkani-English code-mixed social media text, which witnesses several challenges as compared to tagging general normal text. Part-of-Speech Tagging is a primary and an important step for many Natural Language Processing Applications is proposed.. This paper reports work on annotating code-mixed Konkani-English data collected from social media site Facebook, which consists of more than four thousands posts from Facebook and developed automatic Part-of-Speech Taggers for this corpus. Part-of-Speech tagging is considered as a classification problem and we use different classifiers such as CRFs, SVM with different combinations of features.	en_US
dc.publisher	Springer	en_US
dc.subject	Computer Science and Technology	en_US
dc.title	Part-of-speech tagger for Konkani-English code-mixed social media text	en_US
dc.type	Conference article	en_US