Nazia Zaman

Work place: North Dakota State University, Computer Science Department, Fargo, 58078, USA



Research Interests: Social Information Systems, Systems Architecture, Computer systems and computational processes, Data Structures and Algorithms


Nazia Zanman received a B.S. degree from the University of Dhaka, Dhaka, Bangladesh, in 2007, and a M.S. degree from the same university, in 2009. Currently, she is a PhD student of Computer Science Department at the North Dakota State University, Fargo, ND, USA. Her current research focuses on intelligent systems, social networking, and natural language processing.

Author Articles
Entity Extraction from Business Emails

By Juan Li Souvik Sen Nazia Zaman

DOI:, Pub. Date: 8 Aug. 2015

Email still plays an important role in today's business communication thanks to its simplicity, flexibility, low cost, and compatibility of diversified types of information. However processing the large amount of emails received consumes tremendous time and human power for a business. In order to quickly deciphering information and locate business-related information from emails received from a business, a computerized solution is required. In this paper, we have proposed a comprehensive mechanism to extract important information from emails. The proposed solution integrates semantic web technology with natural language processing and information retrieval. It enables automatic extraction of important entities from an email and makes batch processing of business emails efficient. The proposed mechanism has been used in a Transportation company.

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eSMS - a Semantics-assisted Emergency Information System Based on Social Media

By Juan Li Qingrui Li Ashok Ginjala Nazia Zaman

DOI:, Pub. Date: 8 Jul. 2014

Natural and man-made disasters pose an ever-present threat to our society. Providing real time information is vital in emergency management. Current disaster information systems only use and manage relatively limited information, such as, within an organization or with a few organizations which have an agreement on information content and format. As a result, a large amount of potentially precious information and natural volunteer workers are ignored. On the other hand, social media have been used by people to propagate emergent situations. Therefore, in this project, we aim to maximally utilize all of the available emergency-related information from various sources of social media to better manage natural and man-made disasters. In particular, we propose a semantics-extended social search engine that can fetch highly relevant information from social media for emergency management purpose.

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