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Named Entity Recognition (NER) for Social Media Tamil Posts Using Deep Learning with Singular Value Decomposition

EasyChair Preprint no. 6333

5 pagesDate: August 22, 2021

Abstract

The Named Entity Recognition (NER) is a part of Information Extraction (IE) which is an emerging area of research and application that explores how to discover the knowledge (information) from a huge amount of text. There are so many data resources are available on the internet like social media, e-commerce sites, blogs, news portals, personal websites, and so on, where people share their thoughts and opinions in their native language. NER is a process of identifying named entities such as a person, organizations, locations, time, the amount from a given text data (Srinivasan, R., et al., 2019). It was introduced in 1996 at the sixth Message Understanding Conference (MUC-6). The various NER systems were proposed at that time to enhance the information extraction tasks such as Rule-based NER, Machine Learning-based NER, and Hybrid NER (Mansouri, A., et al., 2008). It can be used in many applications such as business intelligence, crime prediction, fraud detection, and recommendation systems.

Keyphrases: deep learning, Named Entity Recognition, short-term memory, social media posts, Tamil Computing, Tamil Text Analysis, Text mining.

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
@Booklet{EasyChair:6333,
  author = {Panner Selvam Kathiravan and Rajiakodi Saranya},
  title = {Named Entity Recognition (NER) for Social Media Tamil Posts Using Deep Learning with Singular Value Decomposition},
  howpublished = {EasyChair Preprint no. 6333},

  year = {EasyChair, 2021}}
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