High user Experience by Providing Relevant News Articles using Topic Modelling

High user Experience by Providing Relevant News Articles using Topic Modelling

  IJETT-book-cover  International Journal of Engineering Trends and Technology (IJETT)          
  
© 2018 by IJETT Journal
Volume-55 Number-1
Year of Publication : 2018
Authors : Santhosh Thiyagarajan
DOI :  10.14445/22315381/IJETT-V55P202

Citation 

Santhosh Thiyagarajan "High user Experience by Providing Relevant News Articles using Topic Modelling", International Journal of Engineering Trends and Technology (IJETT), V55(1),4-7 January 2018. ISSN:2231-5381. www.ijettjournal.org. published by seventh sense research group

Abstract
The digital world where the data grows at an exponential rate where most of them are unstructured in nature. The major task is to categorize them for valuable data extraction. One of the best methods to structure the data is to put them under a topic. The advancement in the computer field gives us various ways to categorize the data corpus such as TF-IDF, MALLET, LDA and so on. Once the model is designed with the appropriate number of topics, then it can be used to predict the topics for the live data. This paper demonstrates the modelling of user based interest based recommendation system to provide relevant articles to the users.

Reference
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Keywords
Latent Dirichlet Allocation, Event Detection, User Experience.