Shaheen Syed got a Paper Accepted at DSAA, Tokyo, Japan

  • shaheen syed DSAA 2017 tokyo

Our ESR Shaheen Syed has got a paper accepted at the 4th IEEE International Conference on Data Science and Advanced Analytics. He will present his paper, entitled “Full-Text or Abstract? Examining Topic Coherence Scores Using Latent Dirichlet Allocation” during the conference to be held in Tokyo on 19-21 October 2017.

The paper examines how different types of textual data, and more specifically fisheries research articles, affects the quality of topics from the topic model Latent Dirichlet Allocation (LDA). LDA can be utilized to automatically uncover topics from documents without the need for prior labeling or annotation of these documents.

The paper can be downloaded below:

Full-Text or Abstract? Examining Topic Coherence Scores Using Latent Dirichlet Allocation

Syed, S., & Spruit, M. (2017). Full-Text or Abstract? Examining Topic Coherence Scores Using Latent Dirichlet Allocation. In The 4th IEEE International Conference on Data Science and Advanced Analytics (pp. 165–174). IEEE. http://doi.org/10.1109/DSAA.2017.61

2017-11-20T18:29:41+00:00 September 7th, 2017|