International Journal of Recent Trends in Engineering & Research

online ISSN

Comparison of Topic Modeling Algorithms

Publication Date : 27/11/2019

DOI : 10.23883/IJRTER.2019.5093.BMCLG

Author(s) :

Avdhi Shah , Urvi Shah , Tilak Satra , Purva Raut.

Volume/Issue :
Volume 5
Issue 11
(11 - 2019)

Abstract :

We present a topic identification system for news, which is based upon an evaluation of similarity between the topics and a large amount of documents in the news database. Our system is able to provide the topics for every news samples. The system implements and compares the two Topic Models, Latent Dirichlet Allocation (LDA) and Latent Semantic Allocation (LSA), on a news database containing eleven thousand documents. The topic models behaviour has been examined on the basis of standard metrics, accuracy and the implementation speed of the algorithms.

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