Journals

    1. Mamta & Ekbal, A. (2025). Quality achhi hai (is good), satisfied! Towards aspect based sentiment analysis in code-mixed language. Computer Speech and Language, Elsevier, 89 (2025) (IF- 3.1, h5-index: 47)
    2. Priya, P., Firdaus, M., & Ekbal, A. (2024). Computational politeness in natural language processing: A survey. ACM Computing Surveys 56 (9), 1-42 (h5 index- 131; IF-16.6)
    3. Priya, P., Firdaus, M. & Ekbal, A. (2024). XeroPol: Emotion-Aware Contrastive Learning for Zero-Shot Cross-Lingual Politeness Identification in Dialogues. IEEE Transactions on Computational Social Systems (IF- 4.5, h5-index: 66)
    4. Mamta & Ekbal, A. (2024). Atmosphere kamaal ka tha (Was Wonderful): A Multilingual Joint Learning Framework for Aspect Category Detection and Sentiment Classification. IEEE Transactions on Computational Social Systems, vol 11(5), 5892-5902 (IF- 4.5, h5-index: 66)
    5. Mishra, K., Firdaus, M. & Ekbal, A. (2024). Please Donate to Save a Life: Inducing Politeness to Handle Resistance in Persuasive Dialogue Agents. In IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol. 32, pp. 2202-2212, 2024 (IF-4.1, h5-index: 74)
    6. Joshi, R.K., Chatterjee, A., & Ekbal, A. (2024). Saliency infused dialogue response generation: Improving task-oriented text generation using feature attribution. Expert Systems with Applications, Elsevier, Volume 255, Part A, 1. (IF- 7.5, h5- index:165)
    7. Bharti, P.K., Navlakha, M., Agarwal, M. and Ekbal, A. (2024). PolitePEER: does peer review hurt? A dataset to gauge politeness intensity in the peer reviews. Language Resources and Evaluation, Springer 58 (4), 1291-1313 (IF- 1.7. h5- index: 33)
    8. Kumar, A., Ghosal, T., Bhattacharjee, S. & Ekbal, A. (2024). Towards automated meta-review generation via an NLP/ML pipeline in different stages of the scholarly peer review process. International Journal on Digital Libraries 25 (3), 493-504
    9. Varshney, D. & Ekbal, A. (2024). Yes, I am afraid of the sharks and also wild lions!: A multitask framework for enhancing dialogue generation via knowledge and emotion grounding. Computer Speech & Language, Elsevier 87, 101645 (IF- 3.1, h5-index: 47)
    10. Phukan, A., Haq Khan, A.A. & Ekbal, A. (2024). QuMIN: quantum multi-moda l data fusion for humor detection. Multimedia Tools and Applications, Springer, 1- 18 (IF- 3, h5-index:105)
    11. Singh, G.V., Verma, A., & Ekbal, A. (2024). MultiSEAO-Mix: A Multimoda l Multitask Framework for Sentiment, Emotion, Support, and Offensive Analysis in Code-Mixed Setting. IEEE Transactions on Computational Social Systems (IF- 4.5, h5-index: 66)
    12. Singh, G.V., Ghosh, S., Firdaus, M., Ekbal, A. & Bhattacharyya, P. (2024). Predicting multi-label emojis, emotions, and sentiments in code-mixed texts using an emojifying sentiments framework. Scientific Reports 14 (1), 12204 (IF-4.3, h5- index: 221)
    13. Das, S.B., Panda, D., Mishra, T., Patra, B., & Ekbal, A. (2024). Multilingual Neural Machine Translation for Indic to Indic Languages. In ACM TALLIP, Vol. 23, No. 5, Article 65
    14. Phukan, A., Pal, S. & Ekbal, A. (2024). Hybrid Quantum-Classical Neural Network for Multimodal Multitask Sarcasm, Emotion, and Sentiment Analysis. IEEE Transactions on Computational Social Systems, vol.11(5), 5740-5750
    15. Kumari, G., Bandyopadhyay, D., Ekbal, A., Pal, S., Chatterjee, A., Vinutha, B.N. (2024). Let’s All Laugh Together: A Novel Multitask Framework for Humor Detection in Internet Memes. IEEE Transactions on Computational Social Systems, vol 11(3), 4385-4395
    16. Kumari, R., Gupta, V., Ashok, N., Ghosal, T. & Ekbal, A. (2024). Emotion aided multi-task framework for video embedded misinformation detection. Multimedia Tools and Applications, Springer, vol 83, 37161-37185
    17. Bharti, P.K., Agarwal, M. & Ekbal, A. (2024). Please be polite to your peers: a multi-task model for assessing the tone and objectivity of critiques of peer review comments, Scientometrics 129 (3), 1377-1413
    18. Varshney, D., Singh, A. & Ekbal, A. (2024). Aspect-level sentiment-controlle d knowledge grounded multimodal dialog generation using generative models for reviews. Multimedia Tools and Applications 83 (10), 29197-29219
    19. Bharti, P.K., Ghosal, T., Agarwal, M. & Ekbal, A. (2024). PEERRec: An AI-based approach to automatically generate recommendations and predict decisions in peer review. International Journal on Digital Libraries, Springer 25 (1), 55-72
    20. Kumari, D. & Ekbal, A. (2024). Enhancing sentiment and emotion translation of review text through MLM knowledge integration in NMT. Journal of Intelligent Information Systems, Springer, 1-25
    21. Zafar, A., Sahoo, S.K., Bhardawaj, H., Das, A. & Ekbal, A. (2024). KI-MAG: A knowledge-infused abstractive question answering system in medical domain, Neurocomputing, Elsevier 571, 127141 (h5 index- 135; IF-6)
    22. Singh, G. V., Firdaus, M., Chauhan, D. S., Ekbal, A., & Bhattacharyya, P. (2024). Zero-shot multitask intent and emotion prediction from multimodal data: A benchmark study. Neurocomputing, Volume 569, Elsevier (h5 index- 135; IF-6)
    23. Mamta & Ekbal, A. (2024). Transformer based multilingual joint learning framework for code-mixed and English sentiment analysis. Journal of Intelligent Information Systems 62 (1), 231-253, Springer
    24. Zafar, A., Sahoo, S.K., Varshney, D., Das, A., & Ekbal, A. (2024). KIMedQA: towards building knowledge-enhanced medical QA models. Journal of Intelligent Information Systems, 1-26, Springer
    25. Varshney, D., Ekbal, A., & Cambria, E. (2024). Emotion-and-knowledge grounded response generation in an open-domain dialogue setting. Knowledge-Based Systems 284, 111173, Elsevier
    26. Gupta, K., Ahmad, A., Ghosal, T. & Ekbal, A. (2024). A BERT-based sequential deep neural architecture to identify contribution statements and extract phrases for triplets from scientific publications. International Journal on Digital Libraries, 1- 28, Springer
    27. Gupta, K., Ghosal, T. & Ekbal, A. (2024). Infusing factual knowledge into pre- trained model for finding the contributions from the research articles. Journal of Information Science, SAGE
    28. Gupta, K., Ahmad, A., Ghosal, T. & Ekbal, A. (2024). SciND: a new triplet-based dataset for scientific novelty detection via knowledge graphs. Int J Digit Libr 25, 639–659
    29. Kumari, G., Sinha, A., Ekbal, A. (2024). Enhancing the fairness of offensive memes detection models by mitigating unintended political bias. J Intell Inf Syst 62, 735– 763 (2024), Springer
    30. Zafar, A., Varshney, D., Kumar Sahoo, S. & Ekbal, A. (2024). Are my answers medically accurate? Exploiting medical knowledge graphs for medical question answering. Applied Intelligence, Springer 54, 2172–2187 (2024)
    31. Joshi, R. K., Chatterjee, A. & Ekbal, A. (2024). Saliency Guided Debiasing: Detecting and mitigating biases in LMs using feature attribution. Neurocomputing, Volume 563, 2024, Elsevier
    32. Firdaus, M., Madasu, A. & Ekbal, A. A Unified Framework for Slot based Response Generation in a Multimodal Dialogue System. Multimedia Tools Application, Springer 83, 11643–11667
    33. Kumari, R., Gupta, V., Ghosal, T. & Ekbal, A. (2023). Emotion Aided Multi-task Framework for Video Embedded Misinformation Detection. In Multimedia Tools and Application, Springer (IF-3.6)
    34. Gupta, K., Ghosal, T. & Ekbal, A. (2023). Infusing Factual Knowledge into BERT for Finding the Contributions from the Research Articles. In Journal of Information Sciences, SAGE (IF-3.1; h5 index: 36)
    35. Chauhan, D.S., Singh, G.V., Ekbal, A. & Bhattacharyya, P. (2023). MHaDiG: A Multilingual Humor-aided Multiparty Dialogue Generation in multimoda l conversational setting. Knowledge-Based Systems 278, 110840, Elsevier (IF-8.8; h5 index: 120)
    36. Varshney, D., Singh, A. & Ekbal, A. (2023). Aspect-level Sentiment-Controlle d Knowledge Grounded Multimodal Dialog Generation using Generative Models for Reviews. Multimedia Tools and Application, Springer, https://doi.org/10.1007/s11042-023-16720-z (h5 index- 96; IF-3.6).
    37. Banik, D., Ekbal, A. & Satapathy, S.C. (2023). Fuzzy Influenced Process to Generate Comparable to Parallel Corpora. ACM Transactions on Asian and Low- Resource Language Information Processing, ACM (IF: 1.5, h5-index: 24)
    38. Firdaus, M., Singh, G.V., Ekbal, A. & Bhattacharyya, P. (2023). Affect-GCN: a multimodal graph convolutional network for multi-emotion with intensity recognition and sentiment analysis in dialogues. Multimedia Tools and Applications, 1-22, Springer (h5 index- 96; IF-3.6)
    39. Ghosh, S., Priyankar, A., Ekbal, A. & Bhattacharyya, P. (2023). A transformer- based multi-task framework for joint detection of aggression and hate on social media data. Natural Language Engineering, Cambridge University Press, 1-21 (Core-A)
    40. Das, S. , Ghosh, S. , Kolya, A. & Ekbal, A. (2023). Unparalleled sarcasm: a framework of parallel deep LSTMs with cross activation functions towards detection and generation of sarcastic statements. Language Resources Evaluation 57(2): 765-802 (2023) (IF: 1.83, h5-index: 28)
    41. Priya, P., Firdaus, M., & Ekbal, A. (2023). A multi-task learning framework for politeness and emotion detection in dialogues for mental health counseling and legal aid. Expert System with Application, Elsevier, 224: 120025 (2023) (IF: 8.5, h5-index: 148)
    42. Varshney, D., Zafar, A., Behera, N.K. & Ekbal, A. (2024). Knowledge grounded medical dialogue generation using augmented graphs. Scientific Reports 13, 3310 (2023). https://doi.org/10.1038/s41598-023-29213-8 (h5 index: 221, IF-4.3)
    43. Singh, G. V., Firdaus, M., Ekbal, A. & Bhattacharyya. P. (2023). EmoInt-Trans: A Multimodal Transformer for Identifying Emotions and Intents in Social Conversations. IEEE/ACM Transaction on Audio, Speech and Language Processing. 31: 290-300 (2023) (h5 index- 69; IF-5.4)
    44. Varshney, D., Tiwari, M., Nagaraja, G.P. & Ekbal, A. (2023). EmoKbGAN : Emotion Controlled Response Generation using Generative Adversarial Network for Knowledge Grounded Conversation. In Plosone, 18(2): e0280458. https://doi.org/ 10.1371/journal.pone.0280458 (h5 index- 212; IF-3.7)
    45. Kumari, M., Ekbal, A. & Bhattacharyya, P. (2023). Exploring Multi-lingual, Multi- task, and Adversarial Learning for Low-resource Sentiment Analysis. In ACM Transactions on Asian and Low-Resource Language Information Processing, Volume 21, Issue 5, Article No.: 104pp 1–19, https://doi.org/10.1145/3514498
    46. Ghosh, S., Ekbal, A., Bhattacharyya, P., Saha, T., Kumar, A., & Srivastava, S. (2023). SEHC: A Benchmark Setup to Identify Online Hate Speech in English. In IEEE Transaction on Computational Social System 10(2): 760-770 (2023)
    47. Kumari, G., Bandyopadhyay, D. & Ekbal, A. (2023). EmoffMeme: Identifying Offensive Memes by leveraging underlying Emotions. Multimedia Tools and Applications, Springer, https://doi.org/10.1007/s11042-023-14807-1 (87)
    48. Ghosh,S., Priyanka, A., Ekbal, A. & Bhattacharyya. P. (2023). Multitasking of sentiment detection and emotion recognition in code-mixed Hinglish data. Knowl. Based System, Elsevier, Volume 260, Issue C https://doi.org/10.1016/j.knosys.2022.110182.
    49. Ghosh, S., Ekbal, A. & Bhattacharyya, P. (2023). VAD-assisted multitask transformer framework for emotion recognition and intensity prediction on suicide notes. Information Processing & Management, Elsevier 60 (2), 103234 (Core-A, h5 index- 69; IF-8.6)
    50. Kumar, S., Ghosal. T. & Ekbal, A. (2023). DeepMetaGen: an unsupervised deep neural approach to generate template-based meta-reviews leveraging on aspect category and sentiment analysis from peer reviews. International Journal on Digital Libraries (IJDL), Springer
    51. Firdaus, M., Ekbal, A., & Cambria, E. (2023). Multitask learning for multilingua l intent detection and slot filling in dialogue systems. Information Fusion 91: 299- 315 (2023), Elsevier (h5 index- 134; IF-14.8)
    52. Mishra, K., Firdaus. M., Ekbal, A. (2023) GenPADS: Reinforcing politeness in an end-to-end dialogue system. PLoS ONE 18(1): e0278323 https://doi.org/10.1371/journal.pone.027832 (h5 index- 212; IF-3.7)
    53. Ahmad, Z., Ekbal, A., Sengupta, S. & Bhattachharyya, P. (2022). Neural Response Generation for Task Completion using Conversational Knowledge Graph. PLosOne, https://doi.org/10.1371/journal.pone.0259238 (IF-3.752; h5 index: 180)
    54. Mishra, K., Firdaus, M. & Ekbal, A. (2022). Please be Polite: Towards building a Politeness Adaptive Dialogue System for Goal-oriented Conversations, Neurocomputing, 94, 242-254, Elsevier (IF-5.719; h5 index: 123)
    55. Misra, K., Firdaus, M. & Ekbal, A. (2022). Predicting politeness variations in Goal- oriented Conversations. IEEE Transaction on Computational Social System, IEEE, doi: 10.1109/TCSS.2022.3156580 (IF-4.747; h5 index: 44)
    56. Singh, G.V., Firdaus, M., Shambhavi, Mishra, S. & Ekbal, A. (2022). Knowing What to Say: Towards knowledge grounded code-mixed response generation for open-domain conversations. Knowledge Based System, Elsevier, 249: 108900 (2022), Elsevier
    57. Chauhan, D.S., Singh, G.V., Arora, A., Ekbal, A. & Bhattacharyya, P. (2022). An emoji-aware multitask framework for multimodal sarcasm detection. Knowledge Based System 257: 109924 (2022), Elsevier (IF: 8.038; h5 index: 107)
    58. Ghosal, T., Kumar, S., Bharti, P. K. & Ekbal, A. (2022). Peer review analyze: A novel benchmark resource for computational analysis of peer reviews, PLosOne, https://doi.org/10.1371/journal.pone.0259238 (IF-3.752; 180)
    59. Ghosh, S., Priyankar, A., Ekbal, A. & Bhattacharyya, P. (2022). A Transformer- based Multi-task Framework for Joint Detection of Aggression and Hate on Social Media Data. Natural Language Engineering, Cambridge University Press, 1-21. doi:10.1017/S1351324923000104 (Core-A)
    60. Firdaus, M., Shandilya, A., Ekbal, A. & Bhattacharyya, P. (2022). Being polite: Modeling politeness variation in a personalized dialog agent. IEEE Transactions on Computational Social Systems, Vol 10, No. 4, 1445-1464
    61. Ghosh, S., Ekbal, A. & Bhattacharyya, P. Deep cascaded multitask framework for detection of temporal orientation, sentiment and emotion from suicide notes. Sci Rep 12, 4457 (2022)
    62. Firdaus, M., Thangavelu, N., Ekbal, A. & Bhattacharyya, P. (2022). I Enjoy Writing and Playing, Do You?: A Personalized and Emotion Grounded Dialogue Agent Using Generative Adversarial Network. In IEEE Transaction on Affective Computing, DOI-0.1109/TAFFC.2022.3155105 (h5 index- 62; IF-16.3)
    63. Firdaus, M., Chauhan, H., Ekbal, A. & Bhattacharyya, P. (2022). EmoSen: Generating Sentiment and Emotion Controlled Responses in a Multimoda l Dialogue System. In IEEE Transaction on Affective Computing 13(3): 1555-1566 (2022). (h5 index- 62; IF-16.3)
    64. Kamila, S., Hasanuzzaman, M., Ekbal, A. & Bhattacharyya, P. (2022). Measuring Temporal Distance Focus From Tweets and Investigating its Association With Psycho-Demographic Attributes. In IEEE Transaction on Affective Computing 13(2): 1086-1097 (2022) (h5 index- 62; IF-16.3)
    65. Akhtar, S., Ghosal, D., Ekbal, A., Bhattacharyya, P. & Kurohashi, S. (2022). All- in-One: Emotion, Sentiment and Intensity Prediction Using a Multi-Task Ensemble Framework. IEEE Trans. Affect. Comput. 13(1): 285-297 (2022) (h5 index- 62; IF- 16.3)
    66. Saikh, T., Ghosal, T., Mittal, A., Ekbal, A., Bhattacharyya, P. (2022). ScienceQA: a novel resource for question answering on scholarly articles. Int. J. Digit. Libr. 23(3): 289-301 (2022), Springer
    67. Ahmad, Z., Sujeeth, V. S. Ekbal, A. (2022). Zero-Shot Hate to Non-Hate Text Conversion Using Lexical Constraints. IEEE Transactions on Computational Social Systems, IEEE, 10.1109/TCSS.2022.3175259 (IF-4.747; h5 index: 44)
    68. Kumari, R., Ashok, N., Ghosal, T. & Ekbal, A. (2024) What the fake? Probing misinformation detection standing on the shoulder of novelty and emotion. Information Processing and Management, Elsevier 59(1): 102740 (2022)
    69. Yadav, S., Jayashree, S. R., Saha, S. & Ekbal, A. (2022). Relation Extraction From Biomedical and Clinical Text: Unified Multitask Learning Framework. In IEEE ACM Trans. Computational Biol. Bioinform. 19(2): 1105-1116 (2022)
    70. Kumari, R., Ekbal, A. (2021): AMFB: Attention based Multi-modal Factorized Bilinear Pooling for Multi-modal Fake News Detection. In: Expert Systems with Applications, Elsevier, https://doi.org/10.1016/j.eswa.2021.115412
    71. Gupta, D, Suman, S., Ekbal, A.(2021): Hierarchical deep multi-modal network for medical visual question answering. In: Expert Systems with Application, Elsevier, 164(1s):113993
    72. Firdaus, M., Thakur, N., Ekbal, A. (2021). Aspect-Aware Response Generation for Multimodal Dialogue System. In ACM Transactions on Intelligent Systems and Technology (TIST) 12 (2), 1-33. 1. (IF-3.971; h5-index: 38)
    73. Sen, S, Hasanuzzaman M., Ekbal A. , Bhattacharyya, P., Way, A. (2021): Neural machine translation of low-resource languages using SMT phrase pair injection. Natural Language Engineering, Cambridge University Press, 271-292 (Core-A)
    74. Ghosal, T., Edithal, V., Ekbal, A., Bhattacharyya, P., Chivukula, S., Tsatsaroni, G. (2021): Is Your Document Novel? Let Attention Guide You. An Attention Based Model For Document Level Novelty Detection. In: Natural Language Engineering Journal, Cambridge University Press, 427-454 (Core-A)
    75. Kumari, R., Nischal, A., Ghosal, T., Ekbal, A. (2021). Misinformation detection using multi-task learning with mutual learning for novelty detection and emotion recognition. In: Information Processing and Management (IPM), Elsevier, 102631/1-15. (Core-A)
    76. Firdaus, M., Golchha., H., Ekbal, A., Bhattacharyya, P. (2021): A Deep Multi-task Model for Dialogue Act Classification, Intent Detection and Slot Filling. In: Cognitive Computation, Springer, 626-645 (h5 index-49; IF-5.418)
    77. Gupta, D., Suman, S. & Ekbal, A. (2021). Hierarchical deep multi-modal network for medical visual question answering. In Expert Syst. Appl. 164: 113993 (2021), Elsevier
    78. Firdaus, M., Shandilya, A.P. & Ekbal, A. (2020). More to Diverse: Generating Diversified Responses in a Task Oriented Multimodal Dialog System. PLosONE, https://doi.org/10.1371/journal.pone.0241271. (IF-3.752; h5 index: 180)
    79. Yadav, S., Ramteke, P., Ekbal, A., Saha, S. & Bhattacharyya, P. (2020). Exploring Disorder-Aware Attention for Clinical Event Extraction. ACM Transactions on Multimedia Computing, Communications, and Applications, https://doi.org/10.1145/3372328
    80. Akhtar, S., Garg, T. & Ekbal, A. (2020). Multi-task Learning for Aspect Term Extraction and Sentiment Classification. In Neurocomputing, Elsevier, https://doi.org/10.1016/j.neucom.2020.02.093
    81. Kapil, P. & Ekbal, A. (2020). A deep neural network based multi-task learning approach to hate speech detection. Knowledge Based System, Elsevier, 210: 106458 (2020)
    82. Ghosh, S., Ekbal, A. & Bhattacharyya, P. (2020). A multitask framework to detect depression, sentiment and multi-label emotion from suicide notes. In Cognitive Computation, Springer, pp. 1-20
    83. Kamila, S., Hasanuzzaman, M., Ekbal, A. & Bhattacharyya, P. (2020). 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
    84. Kamila, S., Hasanuzzaman, M., Ekbal, A. et al. Investigating the impact of emotion on temporal orientation in a deep multitask setting. Sci Rep 12, 493 (2022)
    85. Ahmad, Z., Jindal, R., Ekbal, A. & Bhattachharyya, P. (2020). Borrow from rich cousin: transfer learning for emotion detection using cross lingual embedding. In: Expert Syst. Appl., Elsevier, 139 (2020)
    86. Akhtar, S., Chauhan, D. & Ekbal, A. (2020). A Deep Multi-task Contextual Attention Framework for Multi-modal Affect Analysis. ACM Transaction on Knowledge Discovery from Data, 14(3), 32:1-32
    87. Gupta, D., Ekbal, A. & Bhattacharyya, P. (2020). A Deep Neural Network Framework for English Hindi Question Answering. In: ACM Trans. Asian & Low- Resource Lang. Inf. Processing, 19(2): 25:1-25:22 (2020)
    88. Akhtar, M.S., Ekbal, A., Cambria, E. (2020). How Intense Are You? Predicting Intensities of Emotions and Sentiments using Stacked Ensemble (2020). In: IEEE Computational Intelligence, Vol 15(1),64-75
    89. Banik, D., Ekbal, A., Bhattacharyya, P. & Bhattacharyya, S. (2019). Assembling translations from multi-engine machine translation outputs. Applied Soft Computing, Elsevier, 78: 230-239 (2019)
    90. Roy, S., Mondal, S., Ekbal, A. & Desarkar, M. (2019). Dispersion Ratio based Decision Tree Model for Classification. Expert Syst. Appl., Elsevier, 116: 1-9 (2019)
    91. Yadav, S., Ekbal, A. & Saha, S. (2019). Information theoretic-PSO-based feature selection: an application in biomedical entity extraction. Knowledge and Information System, Springer, 60(3): 1453-1478 (2019)
    92. Firdaus, M., Kumar, A., Ekbal, A. & Bhattacharyya, P. (2019). A Multi-task Hierarchical Approach for Intent Detection and Slot Filling. Knowledge based Systems, Elsevier, ttps://doi.org/10.1016/j.knosys.2019.07.017. (IF-8.038; h5 index: 107)
    93. Yadav, S., Ekbal, A. Saha, S., Kumar, A. & Bhattacharyya, P. (2019). Feature assisted stacked attentive shortest dependency path based Bi-LSTM model for protein-protein interaction. Knowledge Based System, Elsevier, 166: 18-29 (2019)
    94. Akhtar, S., Sawant, P., Sen, S., Ekbal, A. & Bhattacharyya, P. (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
    95. Kamila, S., Hasanuzzaman, M., Ekbal, A. & Bhattacharyya, P. (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
    96. Akhtar, S., Ekbal, A., Narayan, S. & Singh, V. (2018). No, That Never Happened!! Investigating Rumors on Twitter. IEEE Intell. Syst. 33(5):8-15 (2018)
    97. Akhtar, M.S., Gupta, D., Ekbal, A. and Bhattacharyya, P., (2017). Feature selection and ensemble construction: A two-step method for aspect based sentiment analysis. Knowledge-Based Systems, Elsevier, 125, pp.116-135
    98. Alok, A. K., Saha, S. & Ekbal, A. (2017). Semi-supervised clustering for gene- expression data in multiobjective optimization framework. In Int. J. Machine Learning & Cybernetics, Springer, pp. 421-439
    99. Sikdar, U., Ekbal, A. and Saha, S. (2016). A Generalized Framework for Anaphora Resolution in Indian Languages. Knowledge based Systems, Elsevier, Vol. 109: 147-159
    100. Saha, S., Alok, A.K. & Ekbal, A. (2016). Brain image segmentation using semi- supervised clustering. In: Expert Syst. Appl. vol 52. pp. 50-63
    101. Alok, A, K., Saha, S. & Ekbal, A. (2016). Multi-objective semi-supervised clustering for automatic pixel classification from remote sensing imagery. In: Soft Computing, Springer, 4733-4751
    102. Ekbal, A. & Saha, S. (2016). Simultaneous feature and parameter selection using multiobjective optimization: application to named entity recognition. In: International Journal of Machine Learning and Cybernetics, 7, Springer, 597-611
    103. Ekbal, A. & Saha, S. (2015). Joint model for feature selection and parameter optimization coupled with classifier ensemble in chemical mention recognition. In: Knowledge Based Systems, 85, Elsevier, 37-51
    104. Alok, A, K., Saha, S. & Ekbal, A. (2015). A new semi-supervised clustering technique using multi-objective optimization. In: Applied Intelligence, 43(3), Springer, 633-661
    105. Saha, S., Spandana, R., Ekbal, A. & Bandyopadhyay, S. (2015). Simultaneous feature selection and symmetry-based clustering using multiobjective framework. In: Applied Soft Computing, 29, Elsevier, 479-486
    106. Sikdar, U, K., Ekbal, A., Saha, S., Poesio, O, U, M. (2015). Differential evolution-based feature selection technique for anaphora resolution. In: Soft computing, Springer, 2149-2161
    107. Ekbal, A. & Saha, S. (2011). Weighted Vote-Based Classifier Ensemble for Named Entity Recognition: A Genetic Algorithm-Based Approach. In: ACM Transactions on Asian Language Information Processing (ACM TALIP), 10(2), ACM Digital Library, 1-37
    108. Ekbal, A. & Saha, S. (2012). Multiobjective optimization for classifier ensemble and feature selection: an application to named entity recognition. In: International Journal on Document Analysis and Recognition (IJDAR), 15(2), Springer, 143-166
    109. Ekbal, A. & Saha, S.(2011). A multiobjective simulated annealing approach for classifier ensemble: Named entity recognition in Indian languages as case studies. In: Expert System with Application, 6(10), Elsevier, 14760-14772
    110. Ekbal, A., Bonin, F., Saha, Sriparna., Stemle, E., Barbu, E., Cavulli, F., Girardi, C. & Poesio, M. (2011): Rapid Adaptation of NE Resolvers for Humanities Domains using Active Annotation. In: Journal for Language Technology and Computational Linguistics, 26(2), 39-51
    111. Ekbal, A. & Saha, S. (2011): Classifier Ensemble Selection using Genetic Algorithm for Named Entity Recognition. In: Research on Language and Computation, Springer, 8, 73-99
    112. Ekbal, A. & Bandyopadhyay, S. (2011). Named entity recognition in Bengali and Hindi using support vector machine. In: Lingvisticæ Investigationes, John Benjamins Publishing 34 (1), 35-67
    113. Ekbal, A. & Bandyopadhyay (2010). Named entity recognition using support vector machine: A language independent approach. In: International Journal of Electrical, Computer, and Systems Engineering, 4:2:2010, 155-170
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