Publications

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Information Extraction

  • 1

    Compact Residual Learning with Frequency-Based Non-Square Kernels for Small Footprint Keyword Spotting

    Muhammad Abulaish and Rahul Gulia, In Proceedings of the 19th International Conference on Natural Language Processing (ICON), IIIT Delhi, India, December 15-18, 2022, pp. 314-322.

  • 2

    Domain-Specific Keyword Extraction Using Joint Modeling of Local and Global Contextual Semantics

    Muhammad Abulaish, Mohd Fazil, and Muhammed J. Zaki, ACM Transactions on Knowledge Discovery from Data, Article No.: 70, 2022, pp, 1-30.

  • 3

    A Contextual Semantic-Based Approach for Domain-Centric Lexicon Expansion

    Muhammad Abulaish, Mohd. Fazil, and Tarique Anwar, In Proceedings of the 31st Australasian Database Conference (ADC), Melbourne, Australia, LNCS, February 4-7, 2020, pp. 216-224.

  • 4

    A Keyphrase-Based Tag Cloud Generation Framework to Conceptualize Textual Data

    Muhammad Abulaish and Tarique Anwar, International Journal of Adaptive, Resilient and Autonomic Systems, Volume: 4, Issue: 2, IGI Global, USA, 2013, pp. 72-93.

  • 5

    A Supervised Learning Approach for Automatic Keyphrase Extraction

    Muhammad Abulaish and Tarique Anwar, International Journal of Innovative Computing, Information and Control, Volume: 8, Issue: 9, Nov 2012, pp. 7579-7601.

  • 6

    A Statistical Approach for Automatic Keyphrase Extraction

    Muhammad Abulaish, Jahiruddin and Lipika Dey, In Proceedings of the 5th Indian International Conference on Artificial Intelligence (IICAI), Bangalore, India, Dec 14-16, 2011, pp. 1100-1112.

  • 7

    A Web Content Mining Approach for Tag Cloud Generation

    Muhammad Abulaish, and Tarique Anwar, In Proceedings of the 13th International Conference on Information Integration and Web-based Applications & Services (iiWAS), Vietnam, Dec 5-7, 2011, pp. 52-59.

  • 8

    Deep Text Mining for Automatic Keyphrase Extraction from Text Documents

    Muhammad Abulaish, Jahiruddin and Lipika Dey, Journal of Intelligent Systems, Volume: 20, Issue: 4, De Gruyter, Germany, 2011, pp. 327-352.

  • 9

    Knowledge-Based Information Extraction

    Muhammad Abulaish and Qadri N. Naved, In Proceedings of the 5th Saudi Technical Conference and Exhibition, Riyadh, KSA, Vol. II, Jan. 11-14, 2009, pp. 181-187.

  • 10

    Text Mining through Entity-Relationship Based Information Extraction

    Lipika Dey, Muhammad Abulaish, Gaurav Sharma and Jahiruddin, In Proceedings of the Workshop on Biomedical Applications of Web Technologies, Co-located with IEEE/WIC/ACM International Conference on Web Intelligence (WI), Silicon Valley, USA, Nov. 2-5, 2007, pp. 177-180.

Figurative Language Detection

  • 11

    CAT-BiGRU: Convolution and Attention with Bi-directional Gated Recurrent Unit for Self-Deprecating Sarcasm Detection

    Ashraf Kamal and Muhammad Abulaish, Cognitive Computation, Topical Collection: A Decade on Sentic Computing, Vol. 14, Springer, 2021, pp. 91-109.

  • 12

    A Survey of Figurative Language and its Computational Detection in Online Social Networks

    Muhammad Abulaish, Ashraf Kamal, and Mohammed J. Zaki, ACM Transactions on the Web, Volume 14, Issue 1, 2020, pp. 3:1-3:52.

  • 13

    Self-Deprecating Humor Detection: A Machine Learning Approach

    Ashraf Kamal and Muhammad Abulaish, In Proceedings of the 16th International Conference of the Pacific Association for Computational Linguistics (PACLING), Hanoi City, Vietnam, Communications in Computer and Information Science, vol. 1215. Springer, October 11-13, 2019, pp. 1-9.

  • 14

    An LSTM-Based Deep Learning Approach for Detecting Self-Deprecating Sarcasm in Textual Data

    Ashraf Kamal and Muhammad Abulaish, In Proceedings of the 16th International Conference on Natural Language Processing, LTRC, IIIT Hyderabad, India, December 18-21, 2019, pp. 201-210.

  • 15

    Self-Deprecating Sarcasm Detection: An Amalgamation of Rule-Based and Machine Learning Approach

    Muhammad Abulaish and Ashraf Kamal, In Proceedings of the IEEE/WIC/ACM International Conference on Web Intelligence (WI), Santiago, Chile, Dec. 3-6, 2018, pp. 574-579.

Rumor Detection

  • 16

    A Graph-Based Approach Leveraging Posts and Reactions for Detecting Rumors on Online Social Media

    Asimul Haque and Muhammad Abulaish, In Proceedings of the 36th Pacific Asia Conference on Language, Information and Computation (PACLIC), Manila, Philippines, October 20-22, 2022, pp. 1-12.

  • 17

    A Graph-Theoretic Embedding-Based Approach for Rumor Detection in Twitter

    Muhammad Abulaish, Nikita Kumari, Mohd Fazil, and Basanta Singh, In Proceedings of the 18th IEEE/WIC/ACM International Conference on Web Intelligence (WI), Thessaloniki, Greece, October 14-17, 2019, pp. 466-470.

Recommender System

  • 18

    A Hybrid Recommendation Technique using Topic Embedding for Rating Prediction and to Handle Cold-Start Problem

    Vineet K. Sejwal and Muhammad Abulaish, Expert Systems with Applications, Volume 209, 15 December 2022, pp. 118307.

  • 19

    CAMO: A Context-Aware Movie Ontology Generated from LOD and Movie Databases

    Vineet K. Sejwal and Muhammad Abulaish, Multimedia Tools and Applications, Springer Nature, 2020, pp. 1-23.

  • 20

    CRecSys: A Context-Based Recommender System Using Collaborative Filtering and LOD

    Vineet Kumar Sejwal, Muhammad Abulaish, and Jahiruddin, IEEE Access, Volume: 8, August 27, 2020, pp. 158432 - 158448.

  • 21

    A Trust-Based Collaborative Filtering Approach to Design Recommender Systems

    Vineet Kumar Sejwal and Muhammad Abulaish, International Journal of Advanced Computer Science and Applications, Volume: 11, Issue: 10, 2020, pp. 1 - 12.

  • 22

    Trust and Context-based Rating Prediction using Collaborative Filtering: A Hybrid Approach

    Vineet Kumar Sejwal and Muhammad Abulaish, In Proceedings of the 9th International Conference on Web Intelligence, Mining and Semantics (WIMS), Seoul, Korea, June 26-28, 2019, pp. 20:1-20:10.

  • 23

    Context-Based Rating Prediction using Collaborative Filtering and Linked Open Data

    Vineet Kumar Sejwal and Muhammad Abulaish, In Proceedings of the 9th International Conference on Web Intelligence, Mining and Semantics (WIMS), Seoul, Korea, June 26-28, 2019, pp. 19:1-19:9.

Community Detection and Evolution Analysis

  • 24

    OvSbChain: An Enhanced Snowball Chain Approach for Detecting Overlapping Communities in Social Graphs

    Jayati Gulati, Muhammad Abulaish, and Sajid Y. Bhat, International Journal of Advanced Computer Science and Applications, Volume 13, Issue 5, 2022, pp. 1-10.

  • 25

    Scaling Density-Based Community Detection to Large-Scale Social Networks via MapReduce Framework

    Muhammad Abulaish, Ishfaq Majid Bhat, and Sajid Yousuf Bhat, Journal of Intelligent & Fuzzy Systems, vol. 38, no. 2, IOS Press, 2019, pp. 1663-16742.

  • 26

    A Novel Snowball-Chain Approach for Detecting Community Structures in Social Graphs

    Jayati Gulati and Muhammad Abulaish, In Proceedings of the IEEE Symposium on Computational Intelligence and Data Mining (IEEE-CIDM), Xiamen, China, December 6-9, 2019, pp. 1-8.

  • 27

    Modeling Topic Evolution in Twitter: An Embedding-Based Approach

    Muhammad Abulaish and Mohd Fazil, IEEE Access, vol. 6, 2018, pp. 64847-64857.

  • 28

    A Unified Framework for Community Structure Analysis in Dynamic Social Networks

    Sajid Yousuf Bhat, and Muhammad Abulaish, Hema Banati et al. (Eds.) Hybrid Intelligence for Social Networks, Springer, 2017, pp. 71-90.

  • 29

    OCMiner: A Density-Based Overlapping Community Detection Method for Social Networks

    Sajid Y. Bhat and Muhammad Abulaish, Intelligent Data Analysis, Volume: 19, Issue: 4, IOS Press, pp. 917-947, 2015.

  • 30

    HOCTracker: Tracking the Evolution of Hierarchical and Overlapping Communities in Dynamic Social Networks

    Sajid Y. Bhat and Muhammad Abulaish, IEEE Transactions on Knowledge and Data Engineering, Volume: 27, Issue: 4, 2014, pp. 1019-1032.

  • 31

    A Density-Based Approach to Detect Community Evolutionary Events in Online Social Networks

    Muhammad Abulaish and Sajid Y. Bhat, F. Can et al. (Eds.), State of the Art Applications of Social Network Analysis, Lecture Notes in Social Networks, Springer, ISBN: 978-3-319-05911-2, 2014, pp. 189-208. (Extended version of the paper presented at ASONAM 2012)

  • 32

    OCTracker: A Density-Based Framework for Tracking the Evolution of Overlapping Communities in OSNs

    Sajid Y. Bhat and Muhammad Abulaish, In Proceedings of the IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), Istanbul, Turkey, Aug 26-29, 2012, pp. 501-505.

  • 33

    A Density-Based Approach for Mining Overlapping Communities from Social Network Interactions

    Sajid Y. Bhat and Muhammad Abulaish, In Proceedings of the 2nd International Conference on Web Intelligence, Mining and Semantics (WIMS), Craiova, Romania, ACM, June 13-15, 2012, pp. 9:1-9:7.

Social Network Modeling & Analysis

  • 34

    KEvent – A Semantic-Enriched Graph-Based Approach Capitalizing Bursty Keyphrases for Event Detection in OSN

    Sielvie Sharma, Muhammad Abulaish, and Tanvir Ahmad, In Proceedings of the International Workshop on Data Analytics on Social Media, Co-located with the 21st IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technolog, Niagara Falls, Canada, November 17-20, 2022, pp. 1-8.

  • 35

    Analysis and Mining of Online Social Networks - Emerging Trends and Challenges

    Sajid Y. Bhat and Muhammad Abulaish, WIREs Data Mining and Knowledge Discovery, Volume: 3, Issue: 6, John Wiley and Sons, Nov-Dec 2013, pp. 408-444.

  • 36

    A User-Centric Feature Identification and Modeling Approach to Infer Social Ties in OSNs

    Mudassir Wani, Majid A. Alrubaian, and Muhammad Abulaish, In Proceedings of the 15th International Conference on Information Integration and Web-based Applications & Services (iiWAS’13), Vienna, Austria, Dec. 2-4, 2013, pp. 107-114.

  • 37

    Modeling a Web Forum Ecosystem into an Enriched Social Graph

    Tarique Anwar and Muhammad Abulaish, Martin Atzmueller, Alvin Chin, Denis Helic, and Andreas Hotho (Eds.), Ubiquitous Social Media Analysis, LNCS Vol. 8329, ISBN: 978-3-642-45391, Springer, 2013, pp. 152-152. (extended version of the paper presented at MSM 2012)

  • 38

    Mining an Enriched Social Graph to Model Cross-Thread Community Interactions and Interests

    Tarique Anwar and Muhammad Abulaish, In Proceedings of the 3rd International Workshop on Modeling Social Media: Collective Intelligence in Social Media - Co-located with the 23rd ACM Conference on Hypertext and Social Media, Milwaukee, WI, USA, ACM, June 25-28, 2012, pp. 35-38.

Deep Learning

  • 39

    DeepADA: An Attention-Based Deep Learning Framework for Augmenting Imbalanced Textual Datasets

    Amit Kumar Sah and Muhammad Abulaish, In Proceedings of the 19th International Conference on Natural Language Processing (ICON), IIIT Delhi, India, December 15-18, 2022, pp. 304-313.

  • 40

    ADA: An Attention-Based Data Augmentation Approach to Handle Imbalanced Textual Datasets

    Amit Kumar Sah and Muhammad Abulaish, In Proceedings of the 29th International Conference on Neural Information Processing (ICONIP), IIT Indore, November 22-26, 2022, pp. 1-12.

  • 41

    DRCoVe: An AugmentedWord Representation Approach using Distributional and Relational Context

    Md. Aslam Parwez, Muhammad Abulaish, and Mohd. Fazil, In Proceedings of the 16th International Conference on Natural Language Processing, LTRC, IIIT Hyderabad, India, December 18-21, 2019, pp. 220-229.

  • 42

    Multi-Label Classification of Microblogging Texts Using Convolution Neural Network

    Md. Aslam Parwez, Muhammad Abulaish, and Jahiruddin, IEEE Access, vol. 7, 2019, pp. 68678-68691.

  • 43

    A Text Data Augmentation Approach for Improving the Performance of CNN

    Muhammad Abulaish and Amit Kumar Sah, In Proceedings of the MINDS Workshop, 11th International Conference on Communication Systems and Networks (COMSNETS), Bangalore, India, Jan. 7-11, 2019, pp. 625-630.

Emotion AI

  • 44

    Document-Level Sentiment Analysis through Incorporating Prior Domain Knowledge into Logistic Regression

    Nesar Ahmad Wasi and Muhammad Abulaish, In Proceedings of the 19th International Conference on Web Intelligence (WI), Malbourne, Australia, December 14-17, 2020, pp. 1-6.

  • 45

    SentiLangN: A Language-Neutral Graph-Based Approach for Sentiment Analysis in Microblogging Data

    Muhammad Abulaish, Mohammad Rahimi, Habeebullah Ebrahemi, and Amit Kumar Sah, In Proceedings of the 18th IEEE/WIC/ACM International Conference on Web Intelligence (WI), Thessaloniki, Greece, October 14-17, 2019, pp. 461-465.

  • 46

    OMCR: An Opinion-Based Multi-Criteria Ranking Approach

    Muhammad Abulaish, Jahiruddin, and Anjali Bhardwaj, Journal of Intelligent and Fuzzy Systems, vol. 36, no. 1, IOS Press, 2019, pp. 397-411.

  • 47

    Statistical Features Identification for Sentiment Analysis using Machine Learning Techniques

    Ahmad Kamal and Muhammad Abulaish, In Proceedings of the International Symposium on Computational and Business Intelligence (ISCBI), Delhi, India, IEEE, Aug. 24-26, 2013, pp. 178-181.

  • 48

    Mining Feature-Opinion Pairs and their Reliability Scores from Web Opinion Sources

    Ahmad Kamal, Muhammad Abulaish and Tarique Anwar, In Proceedings of the 2nd International Conference on Web Intelligence, Mining and Semantics (WIMS), Craiova, Romania, ACM, June 13-15, 2012, pp. 15:1-15:7.

Socialbot Detection

  • 49

    DeepSBD: A Deep Neural Network Model With Attention Mechanism for SocialBot Detection

    Mohd Fazil, Amit Kumar Sah, and Muhammad Abulaish, IEEE Transactions on Information Forensics and Security, Vol. 16, 2021, pp. 4211-4223.

  • 50

    A Machine Learning Approach for Socialbot Targets Detection on Twitter

    Muhammad Abulaish and Mohd Fazil, Journal of Intelligent & Fuzzy Systems, vol. 40, no. 3, IOS Press, 2021, pp. 4115-4133.

  • 51

    Socialbots: Impacts, Threat-Dimensions, and Defense Challenges

    Muhammad Abulaish and Mohd Fazil, IEEE Technology and Society Magazine, vol. 39, no. 3, IEEE, 2020, pp. 52-61.

  • 52

    A Hierarchical Attention-Based Neural Network Model for Socialbot Detection in OSN

    Mohd Fazil, Amit Kumar Sah and Muhammad Abulaish, In Proceedings of the 19th International Conference on Web Intelligence (WI), Malbourne, Australia, December 14-17, 2020, pp. 1-8.

  • 53

    A Socialbots Analysis-Driven Graph-Based Approach for Identifying Coordinated Campaigns in Twitter

    Mohd. Fazil and Muhammad Abulaish, Journal of Intelligent & Fuzzy Systems, vol. 38, no. 3, IOS Press, 2020, pp. 2961-2977.

  • 54

    Identifying Active, Reactive, and Inactive Targets of Socialbots in Twitter

    Mohd. Fazil, and Muhammad Abulaish, In Proceedings of the IEEE/WIC/ACM International Conference on Web Intelligence (WI), Lepzig, Germany, August 23-26, 2017, pp. 573-580.

Spammer/ Intrusion Detection

  • 55

    A Hybrid Approach for Detecting Automated Spammers in Twitter

    Mohd Fazil and Muhammad Abulaish, IEEE Transactions on Information Forensics and Security, Volume 13, Issue 11, 2018, pp. 2707-2719.

  • 56

    Classifier Ensembles using Structural Features for Spammer Detection in Online Social Networks

    Muhammad Abulaish and Sajid Y. Bhat, Foundations of Computing and Decision Sciences, Volume: 40, Issue: 2, Poznan University of Technology, Poland, 2015, pp. 89-105.

  • 57

    Communities against Deception in Online Social Networks

    Sajid Y. Bhat and Muhammad Abulaish, Computer Fraud and Security, Volume: 2014, Issue: 2, Elsevier, Feb. 2014, pp. 8-16.

  • 58

    Spammer Classification using Ensemble Methods over Structural Social Network Features

    Sajid Y. Bhat, Muhammad Abulaish, and Abdulrahman A. Mirza, In Proceedings of the 14th IEEE/WIC/ACM International Conference on Web Intelligence (WI’14), Warsaw, Poland, Aug. 11-14, 2014, pp. 454-458.

  • 59

    A Generic Statistical Approach for Spam Detection in Online Social Networks

    Faraz Ahmed and Muhammad Abulaish, Computer Communications, Volume: 36, Issue: 10-11, Elsevier, June 2013, pp. 1120-1129.

  • 60

    Community-Based Features for Identifying Spammers in Online Social Networks

    Sajid Y. Bhat and Muhammad Abulaish, In Proceedings of the IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), Niagara Falls, Canada, ACM, Aug. 25-28, 2013, pp. 100-107.

  • 61

    Identification of Sybil Communities Generating Context-Aware Spam on Online Social Networks

    Faraz Ahmad and Muhammad Abulaish, In Proceedings of the 15th Asia-Pacific Web Conference (APWeb), Sydney, Australia, April 4-6, 2013, pp. 268-279.

  • 62

    Graph-Based Learning Model for Detection of SMS Spam on Smart Phones

    Muhammad Z. Rafique and Muhammad Abulaish, In Proceedings of the 8th International Wireless Communications and Mobile Computing Conference (IWCMC) – Trust, Privacy and Security Symposium, Limasol, Cyprus, IEEE, Aug 27-31, 2012, pp. 1046-1051.

  • 63

    A Statistical Pattern Mining Approach for Identifying Wireless Network Intruders

    Nur Al-H. Haldar, Muhammad Abulaish and Syed A. Pasha, In Proceedings of the 5th International Conference on Network Security and Applications (CNSA), Chennai, India, Advances in Intelligent Systems and Computing, Volume: 176, Springer, July 13-15, 2012, pp. 131-140.

  • 64

    An MCL-Based Approach for Spam Profile Detection in Online Social Networks

    Faraz Ahmad and Muhammad Abulaish, In Proceedings of the 11th IEEE International Conference on Trust, Security and Privacy in Computing and Communications (IEEE-TrustCom), Liverpool, UK, IEEE, June 25-27, 2012, pp. 602-608.

  • 65

    An Activity Pattern Based Wireless Intrusion Detection System

    Nur Al-H. Haldar, Muhammad Abulaish, and Syed A. Pasha, In Proceedings of the 9th International Conference on Information Technology: New Generations (ITNG), Las Vegas, Nevada, USA, IEEE, April 16-18, 2012, pp. 846-847.

  • 66

    A Data Mining Framework for Securing 3G Core Network from GTP Fuzzing Attacks

    Faraz Ahmed, Muhammad Z. Rafique and Muhammad Abulaish, In Proceedings of the 7th International Conference on Information Systems Security (ICISS), Kolkata, India, Dec 15-19, 2011, pp. 280-293.

  • 67

    xMiner: Nip the Zero Day Exploits in the Bud

    Muhammad Z. Rafique and Muhammad Abulaish, In Proceedings of the 10th IEEE International Symposium on Network Computing and Applications (IEEE-NCA), Cambridge, MA, USA, Aug 25-27, 2011, pp. 99-106.

Event Detection

  • 68

    A Multi-Attributed Graph-Based Approach for Text Data Modeling and Event Detection in Twitter

    Muhammad Abulaish, Sielvie Sharma, and Mohd Fazil, In Proceedings of the Social Networking Workshop at the 11th International Conference on Communication Systems and Networks (COMSNETS), Bangalore, India, Jan. 7-11, 2019, pp. 703-708. (received best paper award)

  • 69

    Twitter Data Mining for Events Classification and Analysis

    Nausheen Azam, Jahiruddin, Muhammad Abulaish, and Nur Al-Hasan Haldar, In Proceedings of the 2nd International Conference on Soft Computing and Machine Intelligence (ISCMI’15), Hong Kong, IEEE CPS, Nov. 23-24, 2015, pp. 79-83.

Intelligence and Security Informatics

  • 70

    A Multilayer Perceptron Architecture for Detecting Deceptive Cryptocurrencies in Coin Market Capitalization Data

    Harshita Dalal and Muhammad Abulaish, In Proceedings of the 18th IEEE/WIC/ACM International Conference on Web Intelligence (WI), Thessaloniki, Greece, October 14-17, 2019, pp. 438-442.

  • 71

    Ranking Radically Influential Web Forum Users

    Tarique Anwar and Muhammad Abulaish, IEEE Transactions on Information Forensics and Security, Volume: 10, Issue: 6, 2015, pp. 1289-1298.

  • 72

    BiSAL – A bilingual sentiment analysis lexicon to analyze Dark Web forums for cyber security

    Khalid Al-Rowaily, Muhammad Abulaish, Nur Al-Hasan Haldar, and Majed Al-Rubaiana, Digital Investigation, vol. 14, Elsevier, September 2015, pp. 53-62.

  • 73

    Namesake Alias Mining on the Web and its Role Towards Suspect Tracking

    Tarique Anwar and Muhammad Abulaish, Information Sciences, Volume: 276, 2014, pp. 123-145.

  • 74

    A Social Graph Based Text Mining Framework for Chat Log Investigation

    Tarique Anwar and Muhammad Abulaish, Digital Investigation, Volume: 11, Issue: 4, Elsevier, 2014, pp. 349-362.

  • 75

    An MCL-Based Text Mining Approach for Namesake Disambiguation on the Web

    Tarique Anwar and Muhammad Abulaish, In Proceedings of the IEEE/WIC/ACM International Conference on Web Intelligence (WI), Macau, Dec. 4-7, 2012, pp. 40-44.

  • 76

    Identifying Cliques in Dark Web Forums – An Agglomerative Clustering Approach

    Tarique Anwar and Muhammad Abulaish, In Proceedings of the 10th International Conference on Intelligence and Security Informatics (IEEE-ISI), Washington DC, USA, IEEE, June 11-14, 2012, pp. 171-174.

  • 77

    Web Content Mining for Alias Identification: A first step towards suspect tracking

    Tarique Anwar, Muhammad Abulaish and Khaled S. Alghathbar, In Proceedings of the IEEE International Conference on Intelligence and Security Informatics (ISI), Bejing, China, July 10-12, 2011, pp. 195-197.

Graph Mining

  • 78

    An Efficient Subgraph Isomorphism Solver for Large Graphs

    Zubair Ali Ansari, Jahiruddin, and Muhammad Abulaish, IEEE Access, Vol. 9, 2021, pp. 61697-61709.

  • 79

    SubISO: A Scalable and Novel Approach for Subgraph Isomorphism Search in Large Graph

    Muhammad Abulaish, Zubair Ali Ansari, and Jahiruddin, In Proceedings of the 11th International Conference on Communication Systems and Networks (COMSNETS), Bangalore, India, Jan. 7-11, 2019, pp. 102-109.

  • 80

    A Novel Weighted Distance Measure for Multi-Attributed Graph

    Muhammad Abulaish and Jahiruddin, In Proceedings of the 10th Annual ACM India Conference (COMPUTE), Bhopal, India, Nov. 16-18, 2017, pp. 39-47.

  • 81

    Efficient Processing of SPARQL Queries Over GraphFrames

    Ramzan Ali Bahrami, Jayati Gulati, and Muhammad Abulaish, In Proceedings of the IEEE/WIC/ACM International Conference on Web Intelligence (WI), Lepzig, Germany, August 23-26, 2017, pp. 678-685.

Biomedical and Health Informatics

  • 82

    MINDS: A Multi-label Emotion and Sentiment Classification Dataset Related to COVID-19

    Anjali Bhardwaj and Muhammad Abulaish, In Proceedings of the Workshop on Context-aware NLP in eHealth, Co-located with the 19th International Conference on Natural Language Processing (ICON), IIIT Delhi, India, December 15-18, 2022, pp. 1-8.

  • 83

    A Social Media Time-Series Data Analytics Approach for Digital Epidemiology

    Md. Aslam Parwez, Muhammad Abulaish, and Jahiruddin, In Proceedings of the 19th International Conference on Web Intelligence (WI), Malbourne, Australia, Malbourne, Australia, December 14-17, 2020, pp. 1-8.

  • 84

    Exploring Molecular Descriptors and Fingerprints to Predict mTOR Kinase Inhibitors using Machine Learning Techniques

    Chetna Kumari, Muhammad Abulaish, and Naidu Subbarao, IEEE/ACM Transactions on Computational Biology and Bioinformatics, Volume: 18, Issue: 5, 2021, pp. 1902-1913.

  • 85

    Using SMOTE to Deal with Class-Imbalance Problem in Bioactivity Data to Predict mTOR Inhibitors

    Chetna Kumari, Muhammad Abulaish, and Naidu Subbarao, Springer Nature Computer Science 1, Article no. 150 (2020), Springer Nature, pp. 1-12.

  • 86

    DiseaSE: A Biomedical Text Analytics System for Disease Symptom Extraction and Characterization

    Muhammad Abulaish, Md. Aslam Parwez, and Jahiruddin, Journal of Biomedical Informatics, vol. 100 (2019) 103324, pp. 1-15..

  • 87

    Predicting JNK1 Inhibitors Regulating Autophagy in Cancer using Random Forest Classifier

    Chetna Kumari, Naidu Subbarao, and Muhammad Abulaish, bioRxiv, 2018, pp. 1-13, URL: https://doi.org/10.1101/459669

  • 88

    Biomedical Text Analytics for Characterizing Climate-Sensitive Disease

    Md. Aslam Parwez, Muhammad Abulaish and Jahiruddin, In Proceedings of the International Conference on Computational Intelligence and Data Science, Noida, India, Procedia Computer Science, vol. 132, Elsevier, April 7-8, 2018, pp. 1002-1011.

  • 89

    Web-Content Mining for Learning Generic Relations and their Associations from Textual Biological Data

    Muhammad Abulaish and Jahiruddin, Mourad Elloumi and Albert Y. Zomaya (Eds.), Biological Knowledge Discovery Handbook: Preprocessing, Mining and Post-Processing of Biological Data, John Wiley & Sons, ISBN: 9781118132739, 2013, pp. 919-942.

  • 90

    Relation Characterization using Ontological Concepts

    Muhammad Abulaish, In Proceedings of the 8th International Conference on Information Technology: New Generations (ITNG), Las Vegas, Nevada, USA, April 11-13, 2011, pp. 585-590.

  • 91

    A Concept-Driven Biomedical Knowledge Extraction and Visualization Framework for Conceptualization of Text Corpora

    Jahiruddin, Muhammad Abulaish, and Lipika Dey, Journal of Biomedical Informatics, Volume: 43, Issue: 6, Elsevier, 2010, pp. 1020-1035.

  • 92

    Semantic Integration of Information through Relation Mining – Application to Bio-Medical Text Processing

    Lipika Dey, Muhammad Abulaish, Rohit Goyel, and Jahiruddin, In Proceedings of the 2nd International Conference on Pattern Recognition and Machine Intelligence (PReMI), Kolkata, India, LNCS, Springer-Verlag, Dec. 18-22, 2007, pp. 365-372.

  • 93

    Relation Extraction from Texts for Efficient Access to Information – Application to Bio-Medical Text Processing

    Lipika Dey, Muhammad Abulaish and Jahiruddin, In Proceedings of the 3rd Indian International Conference on Artificial Intelligence (IICAI), Pune, India, Dec 17-19, 2007, pp. 1719-1737.

  • 94

    An Ontology-based Pattern Mining System for Extracting Information from Biological Texts

    Muhammad Abulaish and Lipika Dey, In Proceedings of the 10th International Conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing (RSFDGrC), Canada, LNCS-3642, Springer-Verlag, 2005, pp. 420-429.

Digital Forensics

  • 95

    P2DF: A Privacy-Preserving Digital Forensics Framework

    Muhammad Abulaish, Nur Al-Hasan Haldar and Jahiruddin, International Journal of Digital Crime and Forensics (IJDCF), Vol 13, No. 6, 2021, pp. 1-15.

  • 96

    Advances in Digital Forensics Frameworks and Tools: A Comparative Insight and Ranking

    Muhammad Abulaish and Nur Al-Hasan Haldar, International Journal of Digital Crime and Forensics, vol. 10, no. 2, 2018, pp. 95-119.

  • 97

    Data Warehousing Based Computer Forensics Investigation Framework

    Waleed Halboob, Ramlan Mahmod, Muhammad Abulaish, Haider Abbas, and Kashif Saleem, In Proceedings of the 12th International Conference on Information Technology - New Generations (ITNG), Las Vegas, NV, USA , April 13-15, 2015, pp. 163-168.

  • 98

    DigLA - A Digsby Log Analysis Tool to Identify Forensic Artifacts

    Muhammad Yasin and Muhammad Abulaish, Digital Investigation, Volume: 9, Issue: 3-4, Elsevier, 2013, pp. 222-234.

  • 99

    Forensic Analysis of Digsby Log Data to Trace Suspected User Activities

    Muhammad Yasin, Muhammad Abulaish and Muhammad N. N. Elmogy, In Proceedings of the 9th FTRA International Conference on Secure and Trust Computing, Data Management, and Applications (STA), Gwangju, Korea, LNEE 180, Springer, Sep 6-8, 2012, pp. 119-126.

  • 100

    Quaternary Privacy-Levels Preservation in Computer Forensics Investigation Process

    Waleed Halboob, Muhammad Abulaish and Khaled S. Alghathbar, In Proceedings of the 6th International Conference for Internet Technology and Secured Transactions (ICITST), Abu Dhabi, UAE, Dec 11-14, 2011, pp. 777-782.

Data Mining

  • 101

    Clustering Periodic Frequent Patterns Using Fuzzy Statistical Parameters

    Fokrul A. Mazarbhuiya and Muhammad Abulaish, International Journal of Innovative Computing, Information and Control, Volume: 8, Issue: 3B, March 2012, pp. 2113-2124.

  • 102

    Mining Local Association Rules from Temporal Data Set

    Fokrul A. Mazarbhuiya, Muhammad Abulaish, Anjana K. Mahanta, and Tanvir Ahmad, In Proceedings of the 3rd International Conference on Pattern Recognition and Machine Intelligence (PReMI), Delhi, India, LNCS-5909, Springer-Verlag, Dec 16-20, 2009, pp. 255-260.

Document Summarization and Query Answering

  • 103

    A Layered Approach for Summarization and Context Learning from Microblogging Data

    Muhammad Abulaish, Md. Imran Hossain Showrov, and Mohd Fazil, In Proceedings of the 20th International Conference on Information Integration and Web-based Applications & Services (iiWAS), Yogyakarta, Indonesia, Nov. 19-21, 2018, pp. 70-78.

  • 104

    Why a Socialbot is Effective in Twitter? A Statistical Insight

    Mohd Fazil and Muhammad Abulaish, In Proceedings of the 9th International Conference on Communication Systems and Networks (COMSNETS), Social Networking Workshop, Bengaluru, India, January 4-8, 2017, pp. 564-569. (received best paper award)

  • 105

    Overlapping Social Network Communities and Viral Marketing

    Sajid Y. Bhat and Muhammad Abulaish, In Proceedings of the International Symposium on Computational and Business Intelligence (ISCBI), Delhi, India, IEEE, Aug. 24-26, 2013, pp. 243-346.

  • 106

    Opinion-Based Imprecise Query Answering

    Muhammad Abulaish, Tanvir Ahmad, Jahiruddin and Mohammed N. Doja, In Proceedings of the 14th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), Hyderabad, India, LNAI-6119, Part-II, Springer-Verlag, June 21-24, 2010, pp. 238-248.

  • 107

    Automated Summarization and Visualization of Unstructured Text Documents

    Muhammad Abulaish and Khaled S. Alghathbar, In Proceedings of the International Conference on IT and Business Intelligence (ITBI), Nagpur, India, November 12-14, 2010.

  • 108

    A Relation Mining and Visualization Framework for Automated Text Summarization

    Muhammad Abulaish, Jahiruddin and Lipika Dey, In Proceedings of the 3rd International Conference on Pattern Recognition and Machine Intelligence (PReMI), Delhi, India, LNCS-5909, Springer-Verlag, Dec. 16-20, 2009, pp. 249-254.

  • 109

    Feature and Opinion Mining for Customer Review Summarization

    Muhammad Abulaish, Tanvir Ahmad, Jahiruddin, and Mohammed N. Doja, In Proceedings of the 3rd International Conference on Pattern Recognition and Machine Intelligence (PReMI), Delhi, India, LNCS-5909, Springer-Verlag, Dec. 16-20, 2009, pp. 219-224.

  • 110

    Mining Biological Interactions from Biomedical Texts for Efficient Query Answering

    Muhammad Abulaish, Jahiruddin and Lipika Dey, Jake Y. Chen and Stefano Lonardi (Eds.), Biological Data Mining, Chapman & Hall/CRC Data Mining and Knowledge Discovery Series, Taylor and Francis, ISBN: 9781420086843, 2009, pp. 485-527.

  • 111

    A Fuzzy Ontology-Based Text Mining System for Knowledge Acquisition, Ontology Enhancement and Query Answering from Bio-Medical Texts

    Lipika Dey and Muhammad Abulaish, Gary B. Fogel, David W. Corne and Yi Pan (Eds.), Computational Intelligence in Bioinformatics. IEEE Press Series on Computational Intelligence, Wiley/ IEEE Inc., ISBN-9780470105269, 2008, pp. 297-339.

  • 112

    Biological Relation Extraction and Query Answering from Medline Abstracts using Ontology-based Text Mining

    Muhammad Abulaish and Lipika Dey, Data and Knowledge Engineering, Volume: 61, Issue: 2, Elsevier, 2007, pp. 228-262.

  • 113

    Information Extraction and Imprecise Query Answering from Web Documents

    Muhammad Abulaish and Lipika Dey, Web Intelligence and Agent Systems – An International Journal, Volume: 4, Issue: 4, IOS Press, Netherland, 2006, pp. 407-429.

  • 114

    Ontology Enhancement for Including Newly Acquired Knowledge about Concept Descriptions and Answering Imprecise Queries

    Lipika Dey and Muhammad Abulaish, David Taniar and Johanna W. Rahayu (Eds.), Web Semantics and Ontology, IGI Global, USA, ISBN: 9781591409052, 2005, pp. 189-225.

  • 115

    Intelligent Query Processing Using Semantic Web and Ontology

    Muhammad Abulaish and Lipika Dey, Journal of Computer Society of India, Volume: 34, Issue: 2, CSI, 2004, pp. 32-41.

Semantic Web and Ontology

  • 116

    OntoLSA - An Integrated Text Mining System for Ontology Learning and Sentiment Analysis

    Ahmad Kamal, Muhammad Abulaish, and Jahiruddin, Witold Pedrycz and Shyi-Ming Chen (Eds.) Sentiment Analysis and Ontology Engineering, Studies in Computational Intelligence 639, Springer, ISBN: 978-3-319-30317-8, 2016, pp. 399-423.

  • 117

    A Security Information Management Ontology

    Muhammad Abulaish, Syed I. Nabi, Khaled S. Alghathbar and Azeddine Chikh, In Proceedings of the 8th IEEE/FTRA International Conference on Secure and Trust Computing, Data Management, and Applications (STA), Loutraki, Greece, June 28-30, 2011, pp, 201-208.

  • 118

    An Ontology Based Information Security Requirements Engineering Framework

    Azeddine Chikh, Muhammad Abulaish, Syed I. Nabi and Khaled S. Alghathbar, In Proceedings of the 8th IEEE/FTRA International Conference on Secure and Trust Computing, Data Management, and Applications (STA), Loutraki, Greece, June 28-30, 2011, pp, 139-146.

  • 119

    An Ontology Enhancement Framework to Accommodate Imprecise Concepts and Relations

    Muhammad Abulaish, Journal of Emerging Technologies in Web Intelligence, Volume: 1, Issue: 1, Academy Publisher, Finland, 2009, pp. 22-36.

  • 120

    Fuzzy Ontologies for Handling Uncertainties and Inconsistencies in Domain Knowledge Description

    Lipika Dey and Muhammad Abulaish, In Proceedings of the IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) organized as a part of the IEEE World Congress on Computational Intelligence, Hong-Kong, China, June 1-6, 2008, pp. 1366-1373.

  • 121

    A Fuzzy Ontology Generation Framework for Handling Uncertainties and Non-uniformity in Domain Knowledge Description

    Muhammad Abulaish and Lipika Dey, In Proceedings of the International Conference on Computing: Theory and Applications (ICCTA), Kolkata, India, March 5-7, 2007, pp. 287-293.

  • 122

    Ontological Representation for Links into the Future

    Muhammad T. Afzal and Muhammad Abulaish, In Proceedings of the International Conference on Convergence Information Technology (ICCIT), Korea, 2007, pp. 1832-1837.

  • 123

    A Rough-Fuzzy Ontology Generation Framework and Its Application to Bio-medical Text Processing

    Lipika Dey, Muhammad Abulaish, Rohit Goyal and Kumar Shubham, In Proceedings of the 5th Atlantic Web Intelligence Conference (AWIC), Fontainebleau, France. Advances in Soft Computing Series, Volume: 43, Springer Berlin/Heidelberg, June 25-27, 2007, pp. 74–79.

  • 124

    Interoperability among Distributed Overlapping Ontologies – A Fuzzy Ontology Framework

    Muhammad Abulaish and Lipika Dey, In Proceedings of the IEEE/WIC/ACM International Conference on Web Intelligence (WI), Hong Kong, 2006, pp. 397-403.

  • 125

    Enhancing a Biological Concept Ontology to Fuzzy Relational Ontology with Relations Mined from Text

    Lipika Dey and Muhammad Abulaish, In Proceedings of the 5th International Conference on Rough Sets and Current Trends in Computing (RSCTC), Japan, LNCS-4259, Springer-Verlag, 2006, pp. 527-536.

  • 126

    Biological Ontology Enhancement with Fuzzy Relations: A Text-Mining Framework

    Muhammad Abulaish and Lipika Dey, In Proceedings of the IEEE/WIC/ACM International Conference on Web Intelligence (WI), France, 2005, pp. 379-385.

  • 127

    Knowledge Enhancement through Ontology-Gided Text Mining

    Muhammad Abulaish and Lipika Dey, In Proceedings of the 1st International Conference on Pattern Recognition and Machine Intelligence (PReMI), Kolkata, India, LNCS-3776, Springer-Verlag, 2005, pp. 601-604.

  • 128

    A Framework for Extending Fuzzy Description Logic to Ontology Based Document Processing

    Shailendra Singh, Lipika Dey and Muhammad Abulaish, In Proceedings of the Advances in Web Intelligence: 2nd International Atlantic Web Intelligence Conference (AWIC), Cancun, Mexico, LNCS-3034, Springer-Verlag, 2004, pp. 95-104.

  • 129

    Using Part-of-Speech Patterns and Domain Ontology to Mine Imprecise Concepts from Text Documents

    Muhammad Abulaish and Lipika Dey, In Proceedings of the 6th International Conference on Information Integration and Web Based Applications and Services (iiWAS), Jakarta, Indonesia, Sep 27-29, 2004, pp. 91-100.

  • 130

    Ontology Based Fuzzy Deductive System to Handle Imprecise Knowledge

    Muhammad Abulaish and Lipika Dey, In Proceedings of the 4th International Conference on Intelligent Technologies, Chiang Mai, Thailand, 2003, pp. 271-278.

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