Anurag Sarkar

Work place: Northeastern University, Boston, United States



Research Interests: Computational Science and Engineering, Artificial Intelligence, Computer Architecture and Organization, Data Structures and Algorithms


Anurag Sarkar received an M.Sc. in Computer Science from St. Xavier’s College (Autonomous), Kolkata in June 2016. He is currently pursuing a PhD from Northeastern University in Boston, MA, USA. His research interests include game science, artificial intelligence and machine learning.

Author Articles
A Frequency Based Approach to Multi-Class Text Classification

By Anurag Sarkar Debabrata Datta

DOI:, Pub. Date: 8 May 2017

Text classification is a method which involves managing and processing important information that can be categorized into predefined classes within a collection of text data. This method plays a vital role in the field of information processing and information retrieval. Different approaches to text classification specifically based on machine learning algorithms have been discussed and proposed in various research works. This paper discusses a classification approach based on the frequencies of some important text parameters and classifies a given text accordingly into one among multiple categories. Using a newly defined parameter called wf-icf, classification accuracy obtained in a previous work was significantly improved upon.

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