High user Experience by Providing Relevant News Articles using Topic Modelling

Santhosh Thiyagarajan

doi:https://doi.org/10.14445/22315381/IJETT-V55P202

Research Article | Open Access | Download PDF

Volume 55 | Number 1 | Year 2018 | Article Id. IJETT-V55P202 | DOI : https://doi.org/10.14445/22315381/IJETT-V55P202

High user Experience by Providing Relevant News Articles using Topic Modelling

Santhosh Thiyagarajan

Citation :

Santhosh Thiyagarajan, "High user Experience by Providing Relevant News Articles using Topic Modelling," International Journal of Engineering Trends and Technology (IJETT), vol. 55, no. 1, pp. 4-7, 2018. Crossref, https://doi.org/10.14445/22315381/IJETT-V55P202

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.

Keywords

Latent Dirichlet Allocation, Event Detection, User Experience

References

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