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

EasyChair Preprint 6333

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

@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 6333},
  year      = {EasyChair, 2021}}