Sajal Halder (On Study Leave)
Department of Computer Science & Engineering

Publication of Sajal Halder (On Study Leave)

Research Interests
Mr. Sajal Halder's research interests are data mining, periodic behavior mining in large scale graph, recommendation systems, trajectory behavior analysis, anomaly detection, sentimental analysis and real life big data analysis (like as sensor data & GPS data).


Journal Papers

5. Sajal Halder, Md. Samiullah and Young-Koo Lee. Supergraph based Periodic Pattern Mining in Dynamic Social Networks. In the journal of Expert Systems With Applications. Volume 72 Pages 430-442, 2017, SCIE (Impact Factor - 2.981), Publisher: Elsevier.

4. Iram Fatima, Sajal Halder, Muhammad Aamir Saleem, Rabia Batool, Muhammad Fahim, YoungKoo Lee, Sungyoung Lee. Smart CDSS: Integration of Social Media Interaction Engine (SMIE) in Healthcare for Chronic Disease Patients. Multimedia Tools and Applications, pages 1-21, 2013, SCIE (Impact Factor - 1.014), Publisher: Springer.

3. Yongkoo Han, Kisung Park, Donghai Guan, Sajal Halder, and Young-Koo Lee. Topological Similarity based Feature Selection for Graph Classication. In the Computer Journal, bxt123, 2013, SCIE (Impact Factor - 0.755), Publisher: Oxford University Press.

2. Sajal Halder, Yongkoo Han and Young-Koo Lee. Discovering Periodic Patterns using Supergraph in Dynamic Networks. Journal of Research Notes in Information Science (RNIS), Volume 14, 2013, pp.148-151.

1. Md. Rezaul Karim, Sajal Halder , Byeong-Soo Jeong, and Ho-Jin Choi. Efficient Mining Frequently Correlated, Associated-correlated and Independent Patterns Synchronously by Removing Null Transactions. Human Centric Technology and Service in Smart Space,LNEE 182, v.182, no.0, pp.93-103, Publisher: Springer.