Dr. Asif Ekbal

    Journals (Selected)


    NLP/Information Extraction/Text Mining

    1. S. Kamila, M. Hasanuzzaman, A. Ekbal and P. Bhattacharyya (2019). Resolution of grammatical tense into actual time, and its application in Time Perspective study in the tweet space. PLOS ONE, https://doi.org/10.1371/journal.pone.0211872.
    2. Md. Shad Akhtar, Palaash Sawant, Sukanta Sen, Asif Ekbal, Pushpak Bhattacharyya (2019). Improving Word Embedding Coverage in Less-Resourced Languages Through Multi-Linguality and Cross-Linguality: A Case Study with Aspect-Based Sentiment Analysis. ACM Trans. Asian & Low-Resource Lang. Inf. Process. 18(2): 15:1-15:22.
    3. Sabyasachi Kamila, Mohammed Hasanuzzaman, Asif Ekbal, Pushpak Bhattacharyya (2019). Tempo-HindiWordNet: A Lexical Knowledge-base for Temporal Information Processing. ACM Trans. Asian & Low-Resource Lang. Inf. Process. 18(2): 19:1-19:22
    4. Debajyoty Banik, Asif Ekbal, Pushpak Bhattacharyya (2019). Machine Learning Based Optimized Pruning Approach for Decoding in Statistical Machine Translation. IEEE Access 7: 1736-1751.
    5. Debajyoty Banik, Asif Ekbal, Pushpak Bhattacharyya, Siddhartha Bhattacharyya (2019). Assembling translations from multi-engine machine translation outputs. Appl. Soft Comput. 78: 230-239, Elsevier.
    6. Shweta Yadav, Asif Ekbal, Sriparna Saha, Ankit Kumar, Pushpak Bhattacharyya (2019). Feature assisted stacked attentive shortest dependency path based Bi-LSTM model for protein-protein interaction. Knowledge Based System. 166: 18-29, Elsevier.
    7. Md. Shad Akhtar, Asif Ekbal, Sunny Narayan, Vikram Singh (2018). No, That Never Happened!! Investigating Rumors on Twitter. IEEE Intelligent Systems 33(5): 8-15
    8. S. Akhtar, P. Sawant, S. Sen, A. Ekbal and P. Bhattacharyya (2018). Improving Word Embedding Coverage in Less-resource Language through Multi-linguality and Cross-linguality: A Case Study with Aspect based Sentiment Analysis. ACM Transaction on Asian and Low-Resource Language Information Processing (ACM TALLIP)- Accepted.
    9. S. Kamila, M. Hasanuzzaman, A. Ekbal and P. Bhattacharyya (2018). Tempo-HindiWordNet: A Lexical Knowledge-base for Temporal Information Processing. ACM Transaction on Asian and Low-Resource Language Information Processing (ACM TALLIP)- Accepted.
    10. S. Ray, S. Mondal, A. Ekbal and M. Roy (2018). Dispersion Ratio Based Decision Tree Model for Classification. Expert Systems with Application, Elsevier.
    11. S. Akhtar, D. Gupta, A. Ekbal and P.Bhattacharyya (2017). Feature Selection and Ensemble Construction: A Two-step Method for Aspect Based Sentiment Analysis. Knowledge based Systems, Elsevier, Impact factor: 3.325, h5-index: 60.
    12. U. Sikdar, A. Ekbal and S. Saha (2016). A Generalized Framework for Anaphora Resolution in Indian Languages. Knowledge based Systems, Elsevier, Impact factor: 3.325, h5-index: 60.
    13. Asif Ekbal and Sriparna Saha (2015).  Joint model for feature selection and parameter optimization coupled with classifier ensemble in chemical mention recognition, Knowledge Based Systems, Elsevier, Vol. 85: 37-51, Impact factor: 3.058, h5-index: 54.
    14. Krallinger, M., Rabal, O., Leitner, F., Vazquez, Sikdar, U., K., Ekbal, A. ,& Segura-Bedmar, I. (2015). The CHEMDNER Corpus of Chemicals and Its Annotation Principles, J. Cheminformatics, 7(S-1): S2 (2015), Springer, Impact factor: 4.55, h5-index: 24
    15. U. Sikdar, A. Ekbal, S. Saha, O. Uryupina andMassimo Poeiso(2015). Differential Evolution based Feature Selection Technique for Anaphora Resolution. Soft Computing, Vol 19(8), PP. 2149-2161, Springer. Impact factor: 1.304, h5-index: 35
    16. U. Sikdar, A. Ekbal and S. Saha (2015). MODE: Multiobjective Differential Evolution for Feature Selection and Classifier Ensemble”, Soft Computing, Springer(2015),Volume 19,Issue 12, pp 3529-3549. Impact factor: 1.304, h5-index: 35
    17. S. Saha, A. Ekbal, U.K. Sikdar (2015). Named Entity Recognition and Classification in Biomedical Text Using Classifier Ensemble. International Journal of Data Mining and Bioinformatics, Volume 11, Issue 4, March 2015, Pages 365-391. Impact factor: 0.681, h5-index: 11
    18. A. Ekbal and S. Saha (2014). On Active Annotation for Named Entity Recognition from Indian Language and Biomedical Domain. Journal of Machine Learning and Cybernatics, Springer, h5-index: 25
    19. U. Sikdar, A. Ekbal and S. Saha (2014). Entity Extraction in Biochemical Text using Multiobjective Optimization. Computing and Systems, Volume 18, Issue 3, (Selected from CICLING; h5-index :17).
    20. A. Ekbal and S. Saha (2014). Simultaneous Feature and Parameter Selection Using Multiobjective Optimization: Application to Named Entity Recognition. International Journal of Machine Learning and Cybernetics, DOI 10.1007/s13042-014-0268-7, Springer,  h5-index: 25.
    21.  A. Ekbal and S. Bandyopadhyay (2013). Named Entity Recognition in Bengali using System Combination. Lingvisticae Investigationes,  Vol 37(1), PP. 1-22, John Benjamin’s Publishing Company.
    22. Asif Ekbal and Sriparna Saha (2013). Stacked Ensemble Coupled with Feature Selection for Biomedical Entity Extraction. Knowledge Based Systems, volume (46), PP. 22–32, Elsevier. Impact factor: 4.01, h5-index: 54.
    23. U. Sikdar, A. Ekbal, S. Saha, O. Uryupina and Massimo Poeiso (2013). Coreference Resolution System for Bengali: An Experiment with Domain Adaptation. In Computing and Systems, 17(2) (Selected from CICLING; h5-index :17).
    24.  A. Ekbal, S.Saha and U. Sikdar (2013). Biomedical Named Entity Extraction: Some Issues of Corpus Compatibilities. Springer Plus, Springer,  h5-index :16
    25. A. Ekbal, S. Saha (2013). Combining Feature Selection and Classifier Ensemble using a Multiobjective Simulated Annealing Approach: Application to Named Entity Recognition. Soft Computing, Vol. 17(1), PP. 1-16, Springer, Impact factor: 1.88, h5-index: 35.
    26. A. Ekbal, S. Saha (2013). Simulated Annealing Based Classifier Ensemble Techniques: Application to Part of Speech Tagging. Information Fusion, Vol 14(3), PP. 288-300, Elsevier. Impact factor: 1.467, h5-index: 33.
    27. S. Saha, A. Ekbal (2013). Combining Multiple Classifiers using Vote based Classifier Ensemble Technique for Named Entity Recognition. Data & Knowledge Engineering, Vol 85(0), PP. 15 – 39, Impact factor: 1.422, h5-index: 29.
    28. A. Ekbal, S. Saha, Md. Hasanuzzaman, A. Majumder (2013). Bio-molecular Event Extraction using A GA based Classifier Ensemble Technique. International Journal of Computer Information Systems and Industrial Management (IJCISIM), 5(2013), 631-641. h5-index: 6
    29. A. Ekbal and S. Saha (2012). Multiobjective Optimization for Classifier Ensemble and FeatureSelection: An Application to Named Entity Recognition, International Journal on Document Analysis and Recognition (IJDAR), Vol. 15(2), PP. 143-166, Springer, h5-index: 20
    30. A. Kolya, A. Ekbal and S. Bandyopadhyay (2012). A Hybrid Approach for Event Extraction. In POLIBITS, Vol.46(2012), PP. 55-59, (Selected from CICLING; h5-index :17).
    31. A. Ekbal, F. Bonin, S. Saha, E. Stemle, E. Barbu, F. Cavulli, C. Girardi, F. Nardelli and M.Poesio (2011). Rapid Adaptation of NE Resolvers for  Humanities Domains using Active Annotation. Journal for Language Technology and Computational Linguistics (JLCL), 26 (2), PP. 39-51.
    32.  A. Ekbal and S. Bandyopadhyay (2011). Named Entity Recognition in Bengali and Hindi using Support Vector Machine. Lingvisticae Investigationes, Vol. (34), Number (1), PP. 35-67, John Benjamins Publishing Company. 
    33. A. Ekbal and S. Saha (2011).  A Multiobjective Simulated Annealing Approach for Classifier Ensemble: Named Entity Recognition in Indian Languages as Case Studies. Expert Syst. Appl. 38(12): PP. 14760-14772 (2011), Elsevier.  Impact factor : 2.203, h5-index: 91.
    34. A.Ekbal and S. Saha (2011). Weighted Vote-Based Classifier Ensemble for Named Entity Recognition: A Genetic Algorithm-Based Approach. ACM Transactions on Asian Language Information Processing (ACM TALIP), Vol. 2(9), ACM, DOI = 10.1145/1967293.1967296 http://doi.acm.org/10.1145/1967293.1967296.
    35. A. Ekbal and S. Saha (2010). Classifier Ensemble Selection Using Genetic Algorithm for Named Entity Recognition. Research on Language and Computation (RLC), Vol. (8), PP. 73-99, Springer. h5-index: 8.
    36. A. Ekbal and S. Bandyopadhyay (2010). Named Entity Recognition using Appropriate Unlabeled Data, Post-processing and Voting. In Informatica, Volume (34), Number (1), PP.55-76. h5-index: 15.
    37. A. Ekbal and S. Bandyopadhyay (2010). A Multiengine NER System with Context Pattern Learning and Post-processing Improves System Performance. International Journal of Computer Processing of Languages (IJCPOL), Vol. 22(2 and 3), World Scientific Press, Singapore, Volume (22:2-3), PP.171-204.
    38. A. Ekbal and S. Bandyopadhyay (2009). A Conditional Random Field Approach for Named Entity Recognition in Bengali and Hindi. Linguistic Issues in Language Technology (LiLT), Volume (2:1), November 2009, PP.1-44, CSLI Publication, Stanford University.
    39. A. Ekbal and S. Bandyopadhyay (2008). A Web-based Bengali News Corpus for Named Entity Recognition. Language Resources and Evaluation (LRE) Journal, Springer, Vol. 42(2), PP.173-182. . h5-index: 23.
    40. A. Ekbal, R. Haque and S. Bandyopadhyay (2008). Maximum Entropy Based Bengali Part of Speech Tagging. In Advances in Natural Language Processing and Applications, Research in Computing Science (RCS) Journal, Vol. (33),PP. 67-78 (Selected from CICLING,  h5-index: 17).
    41. A. Ekbal, S. Naskar and S. Bandyopadhyay (2007). Named Entity Recognition and Transliteration in Bengali. In Named Entities: Recognition, Classification and Use, Special Issue of LingvisticaeInvestigationes Journal, Satoshi Sekine and Elisabete Ranchhod (Eds.),Vol.30:1 (2007), PP. 95-114, John Benjamins Publishing Company.
    42. A. Ekbal, S. Naskar and S. Bandyopadhyay (2007). Named Entity Transliteration. Computer Processing of Languages (IJCPOL), Vol. 20(4), PP. 289-310, World Scientific Press, Singapore.

    Bi-informatics, Clustering and its Applications

    1. S. Saha, A. Alok and A. Ekbal (2016). Brain Image Segmentation using Semi-supervised Clustering. Expert Systems with Applications, Vol. 52, PP. 50-63, Elsevier. Impact factor: 2.240, h5-index: 91.
    2. S. Saha, R. Spandana, A. Ekbal, S. Bandyopadhyay (2015). Simultaneous Feature Selection and Symmetry based Clustering using Multiobjective Framework. Appl. Soft Computing, Elsevier, 29: 479-486, Impact factor, 2.679, h5-index: 65.
    3. A. Alok, S. Saha and A. Ekbal (2015). Semi-Supervised Clustering for Gene-Expression Data in Multiobjective Optimization Framework.  International Journal of Machine Learning and Cybernetics, Pages 1-19, DOI:10.1007/s13042-015-0335-8. h5-index: 25.
    4. A. Alok, S. Saha and A. Ekbal (2015). A New Semi-supervised Clustering Technique using Multi-objective Optimization. Applied Intelligence, Volume 43, Issue 3, Pages 633-661. Impact factor: 1.8, h5-index: 24.
    5. A. Alok, S. Saha and A. Ekbal (2015). Multi-objective Semi-supervised Clustering for Automatic Pixel Classification from Remote Sensing Imagery.  Soft Computing, Pages 1-19, doi:10.1007/s00500-015-1701-x. Impact factor: 1.304, h5-index: 35.
    6. S. Saha, A. Alok and A. Ekbal (2015). Use of Semi-supervised Clustering and Feature Selection Techniques for Gene-Expression Data. IEEE Journal of Biomedical and Health Informatics (Retitled from the IEEE Transactions on Information Technology in Biomedicine (T-ITB), doi: 10.1109/JBHI.2015.2451735. Impact factor: 2.072, h5-index: 16.
    7. S. Roy, S. Mondal, A. Ekbal (2015). CRDT: Correlation Ratio Based Decision Tree Model for Healthcare Data Mining. CoRR abs/1509.07266 (2015).
    8. S. Saha, A. Ekbal, A.Alok and R. Spandana (2014). Feature Selection and Semi-Supervised Clustering Using Multiobjective Optimization. SpringerPlus, Vol (3). h5-index: 16.
    9. S. Saha, R. Spandana, A. Ekbal and S. Bandyopadhyay (2014). Simultaneous Feature Selection and Symmetry Based Clustering using Multiobjective Framework. Applied Soft Computing, Vol. 29, April 2015, Pages 479-486, ISSN 1568-4946. Impact factor: 2.679, h5-index: 65.
    10. S. Saha, A. Ekbal, K. Gupta, S. Bandyopadhyay (2013). Gene expression Data Clustering using a Multiobjective Symmetry based Clustering Technique. Comp. in Bio. and Med., Vol. 43(11): 1965-1977, Elsevier. . Impact factor: 1.162, h5-index: 30.