Muhammad Asif Hossain Khan

Work place: Department of Computer Science & Engineering, University of Dhaka



Research Interests: Computational Science and Engineering, Image Compression, Image Manipulation, Image Processing, Information Retrieval, Data Structures and Algorithms


Muhammad Asif Hossain Khan has completed both B.Sc. and M.Sc. degree in CSE from the University of Dhaka. He also completed PhD from the University of Tokyo, Japan. Currently, he is working as an Associate Professor at the Department of Computer Science and Engineering, University of Dhaka. His research interests include NLP, Information Retrieval, Image Processing, and Machine Learning.

Author Articles
A Rule Based Extractive Text Summarization Technique for Bangla News Documents

By Partha Protim Ghosh Rezvi Shahariar Muhammad Asif Hossain Khan

DOI:, Pub. Date: 8 Dec. 2018

News summarization is a process of distilling the most important information from a news document in a precise way. For the advancement of Internet nowadays almost all of the Bangla newspapers have their online versions, and people of this era like to read newspaper from website using Internet. But large amount of electronic news content is a burden for human to come out with valuable information. For mitigating this pain point, this paper proposes an automatic method to summarize Bangla news document. In this proposed approach, graph based sentence scoring feature is introduced for the first time for Bangla news document summarization. After analyzing vast amount of Bangla news document 12 sentence scoring features have been introduced for calculating score of a sentence. An improved summary generation method has also been proposed which remove the redundant information from summary. The result is evaluated using a standard summary evaluation tool called ROUGE, and found proposed method outperforms all existing methods used in Bangla news summarization.

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