Santanu Phadikar

Work place: Department of Computer Science and Engineering, Maulana Abul Kalam Azad University of Technology, West Bengal-700064, India



Research Interests: Computational Learning Theory, Natural Language Processing, Image Compression, Image Manipulation, Image Processing, Data Structures and Algorithms


Dr. Santanu Phadikar is currently working as an Associate Professor in the department of Computer Science and Engineering, Maulana Abul Kalam Azad University of Technology, West Bengal, India. He has passed his graduation from Vidyasagar University and completed his master degrees from University of Calcutta. He has received his Ph.D degree from Bengal Engineering and Science University, Shibpur, West Bengal, India. He has received University Gold Medal for securing highest marks in gradation in his subject. He has also received National Scholarship for higher study. He has served Vidyasagar University as a Lecture of Computer Science from 2002 to 2006. After that he is serving this University. He is working in the field of Smart Farming, Natural Language Processing, Machine Learning, Voice Processing and Image Processing etc. He is currently running the project ISEA-II as Chief Investigator.

Author Articles
A Novel System for Generating Simple Sentences from Complex and Compound Sentences

By Bidyut Das Mukta Majumder Santanu Phadikar

DOI:, Pub. Date: 8 Jan. 2018

In the field of natural language processing, simple sentence has a great importance; especially for multiple choice question generation, automatic text summarization, opinion mining, machine translation and information retrieval etc. Most of these tasks use simple sentences and include a sentence simplification module as pre-processing or post-processing task. But dedicated tasks for sentence simplification are hardly found. Here we have proposed a novel system for generating simple sentences from complex and compound sentences. Our proposed system is an initiative for simplifying sentence by converting complex and compound sentences into simple ones. Along with this the system classifies the simple sentences of an input corpus from other types of sentences. To generate simple sentences from complex and compound sentences we have proposed a novel algorithm which takes the dependency parsing of the input text and produce simple sentences as output. The experimental result demonstrates that the proposed technique is a promising one.

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