BaNeP: An End-to-End Neural Network Based Model for Bangla Parts-of-Speech Tagging
Ovi, Jesan Ahammed, Islam, Md Ashraful, Karim, Md Rezaul, IEEE Access, 2022
Published in IEEE Access (Vol. 10, pp. 102753–102769).
Bangla NLP
BaNeL: an encoder-decoder based Bangla neural lemmatizer
Islam, Md Ashraful, Towhiduzzaman, Md, Bhuiyan, Md, Islam, Tauhidul, Maruf, Abdullah Al, Ovi, Jesan Ahammed, SN Applied Sciences, 2022
Published in SN Applied Sciences (Vol. 4, No. 5, pp. 1–15).
Bangla NLP
Weighted frequent sequential pattern mining
Islam, Md Ashraful, Rafi, Mahfuzur Rahman, Azad, Al-amin, Ovi, Jesan Ahammed, Applied Intelligence, 2022
Published in Applied Intelligence (Vol. 52, No. 1, pp. 254–281).
Sequential Pattern Mining
Mining High Utility Subgraphs
Alam, Md Tanvir, Roy, Amit, Ahmed, Chowdhury Farhan, Islam, Md Ashraful, Leung, Carson K, ICDMW, 2021
Presented at 2021 International Conference on Data Mining Workshops (ICDMW), pp. 566–573.
Graph Mining
Weighted Clickstream Mining Using Pre-order Linked Web-Access Pattern Tree
Naser, Abu, Sultana, Nusrat, Islam, Md Ashraful, Ovi, Jesan Ahammed, INCET, 2021
Presented at 2021 2nd International Conference for Emerging Technology (INCET), pp. 1–11.
Clickstream Mining
WeFreS: weighted frequent subgraph mining in a single large graph
Ashraf, Nahian, Haque, Riddho Ridwanul, Islam, Md, Ahmed, Chowdhury Farhan, Leung, Carson K, Mai, Jiaxing Jason, Wodi, Bryan H, ibai publishing, 2019
Book chapter published in 2019.
Graph Mining
An efficient approach for sequential pattern mining on GPU using CUDA platform
Nuruddin, Shah Mohammed, Islam, Md Didarul, Alam, Md Shafiqul, Ovi, Jesan Ahammed, Islam, Md Ashraful, ISMSIT, 2020
Presented at 2020 4th International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT), pp. 1–9.
GPU / CUDA
WFSM-MaxPWS: an efficient approach for mining weighted frequent subgraphs from edge-weighted graph databases
Islam, Md Ashraful, Ahmed, Chowdhury Farhan, Leung, Carson K, Hoi, Calvin SH, PAKDD, 2018
Presented at Pacific-Asia Conference on Knowledge Discovery and Data Mining, pp. 664–676.
Graph Mining