This book comprises select proceedings of the 7th International Conference on Data Science and Engineering (ICDSE 2021). The contents of this book focus on responsible data science. This book tries to integrate research across diverse topics related to data science, such as fairness, trust, ethics, confidentiality, transparency, and accuracy. The chapters in this book represent research from different perspectives that offer novel theoretical implications that span multiple disciplines. The book will serve as a reference resource for researchers and practitioners in academia and industry.
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This book comprises select proceedings of the 7th International Conference on Data Science and Engineering (ICDSE 2021). This book tries to integrate research across diverse topics related to data science, such as fairness, trust, ethics, confidentiality, transparency, and accuracy.
Les mer
End-to-end Hierarchical Approach for Emotion Detection in short texts.- Towards an Enhanced Understanding of Bias in Pre-trained Neural Language Models: A Survey  with Special Emphasis on Affective Bias.- Exploring Rawlsian Fairness for K-Means Clustering.- Hybrid Explainable Educational Recommender using Self Attention and Knowledge Based Systems for E-Learning in MOOC Platforms.- An Improved Recommendation System with Aspect-Based Sentiment Analysis.- Exploring Biomarker Identification and Mortality Prediction of COVID-19 Patients using ML Algorithms.- COVID-19 cases prediction based on LSTM and SIR model using social media.- Joint Geometrical and Statistical Alignment using Triplet loss for Deep Domain Adaptation.- Virtual Try-On Using Style Transfer.- Attention Mechanism in Convolutional Recurrent Neural Network for Improving Recognition Accuracy in Printed Devanagari Text.
Les mer
This book comprises select proceedings of the 7th International Conference on Data Science and Engineering (ICDSE 2021). The contents of this book focus on responsible data science. This book tries to integrate research across diverse topics related to data science, such as fairness, trust, ethics, confidentiality, transparency, and accuracy. The chapters in this book represent research from different perspectives that offer novel theoretical implications that span multiple disciplines. The book will serve as a reference resource for researchers and practitioners in academia and industry.
Les mer
Includes latest research in AI and ML on responsible data science Provides immediate reference material to data scientists working in multiple domains Distinguishes new pathways in data science related to unboxing AI algorithms
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Produktdetaljer

ISBN
9789811944529
Publisert
2022-11-15
Utgiver
Vendor
Springer Verlag, Singapore
Høyde
235 mm
Bredde
155 mm
Aldersnivå
Research, P, 06
Språk
Product language
Engelsk
Format
Product format
Innbundet

Om bidragsyterne

Jimson Mathew is currently a professor in the Department of the Computer Science and Engineering, Indian Institute of Technology Patna, India. He received a master's in computer engineering from Nanyang Technological University, Singapore, and a Ph.D. degree in computer engineering from the University of Bristol, Bristol, UK. He has held positions with the Centre for Wireless Communications, the National University of Singapore, Bell Laboratories Research Lucent Technologies North Ryde, Australia, Royal Institute of Technology KTH, Stockholm, Sweden, and Department of Computer Science, University of Bristol, UK. He is a Senior Member of IEEE. He has previously served as Guest Editor for ACM TECS. He also regularly serves on the program committee of top international conferences and holds multiple patents. His research interests include fault-tolerant computing, computer vision, machine learning, and IoT systems.

Santhosh Kumar G is a full Professor at the Department of Computer Science, Cochin University of Science and Technology, Kerala, India. His research interests include cyber-physical systems, machine learning, and natural language processing. He is a senior member of the IEEE and the ACM, published several publications, and co-authored a book on Data Science.

Deepak P is an Associate Professor of Computer Science at Queen’s University Belfast (UK) and an adjunct faculty member at IIT Madras (India). His research interests include ethics for machine learning, natural language processing, and information retrieval. He is a senior member of the IEEE and the ACM and has authored over 100 publications, authored/edited three books, and is an inventor on over 10 patents.

Joemon M Jose has been an active researcher in information retrieval (IR) since 1993 and has published over 300 journal and conference articles on information retrieval. He, along with co-authors, has received best paper/student paper awards at leading conferences, including ACMSIGIR, IIiX, CHIIR, MMM, and the BCS ECIR. He has supervised, as primary supervisor, 20 Ph.D. students and over 20 RAs and postdoctoral researchers. He has chaired several conferences, was one of the program committee chairs for the ECIR 2017 and 2020 conferences, regularly acts as a primary reviewer for A/A* conferences, and has attracted over 3M pounds in research funding.