Md. Sadekur Rahman

Work place: Department of CSE, Daffodil International University, Dhaka, Bangladesh

E-mail: sadekur738@gmail.com

Website:

Research Interests: Artificial Intelligence, Natural Language Processing, Pattern Recognition, Data Mining

Biography

Md. Sadekur Rahman is pursuing his Ph.D. at University Sains Islam Malaysia on Ontology and knowledge management. He obtained his B.Sc. and M.Sc. degree in Applied Mathematics & Informatics from Peoples' Friendship University of Russia. Now he is working as a Senior Lecturer at the Department of Computer Science and Engineering in Daffodil International University. He has a number of publications in international and national journals and conference proceedings. His research interest includes Data Mining, Artificial Intelligence, Pattern Recognition, and Natural Language Processing.

Author Articles
An Exploratory Approach to Find a Novel Metric Based Optimum Language Model for Automatic Bangla Word Prediction

By Md. Tarek Habib Abdullah Al-Mamun Md. Sadekur Rahman Shah Md. Tanvir Siddiquee Farruk Ahmed

DOI: https://doi.org/10.5815/ijisa.2018.02.05, Pub. Date: 8 Feb. 2018

Word completion and word prediction are two important phenomena in typing that have intense effect on aiding disable people and students while using keyboard or other similar devices. Such auto completion technique also helps students significantly during learning process through constructing proper keywords during web searching. A lot of works are conducted for English language, but for Bangla, it is still very inadequate as well as the metrics used for performance computation is not rigorous yet. Bangla is one of the mostly spoken languages (3.05% of world population) and ranked as seventh among all the languages in the world. In this paper, word prediction on Bangla sentence by using stochastic, i.e. N-gram based language models are proposed for auto completing a sentence by predicting a set of words rather than a single word, which was done in previous work. A novel approach is proposed in order to find the optimum language model based on performance metric. In addition, for finding out better performance, a large Bangla corpus of different word types is used.

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