Named Entity Popularity Determination using Ensemble Learning

Vikram Karthikeyan, B Shrikara Varna, Amogha Hegde, Govind Satwani, Shambhavi B R, Jayarekha P, Ranjan Samal


Abstract
Determining the popularity of a Named Entity after completion of Named Entity Recognition (NER) task finds many applications. This work studies Named Entities of Music and Movie domains and solves the problem considering relevant 11 features. Decision Trees and Random Forests approaches were applied on the dataset and the latter algorithm resulted in acceptable accuracy.
Anthology ID:
2020.icon-workshop.4
Volume:
Proceedings of the Workshop on Joint NLP Modelling for Conversational AI @ ICON 2020
Month:
December
Year:
2020
Address:
Patna, India
Editors:
Praveen Kumar G S, Siddhartha Mukherjee, Ranjan Samal
Venue:
ICON
SIG:
Publisher:
NLP Association of India (NLPAI)
Note:
Pages:
27–32
Language:
URL:
https://aclanthology.org/2020.icon-workshop.4
DOI:
Bibkey:
Cite (ACL):
Vikram Karthikeyan, B Shrikara Varna, Amogha Hegde, Govind Satwani, Shambhavi B R, Jayarekha P, and Ranjan Samal. 2020. Named Entity Popularity Determination using Ensemble Learning. In Proceedings of the Workshop on Joint NLP Modelling for Conversational AI @ ICON 2020, pages 27–32, Patna, India. NLP Association of India (NLPAI).
Cite (Informal):
Named Entity Popularity Determination using Ensemble Learning (Karthikeyan et al., ICON 2020)
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PDF:
https://aclanthology.org/2020.icon-workshop.4.pdf