Recent Developments in Machine Learning and Data Analytics: Ic3 2018

ISBN-13: 9789811312793 / Angielski / Miękka / 2018 / 530 str.

Jugal Kalita; Valentina Emilia Balas; Samarjeet Borah

Opis

This book presents high-quality papers from an international forum for research on computational approaches to learning. Further, it features work that shows how to apply learning methods to solve important application problems as well as how machine learning research is conducted.

Spis treści

Chapter 1: MaNaDAC:An Effective Alert Correlation Method.- Chapter 2: WSD for Assamese Language.- Chapter 3: Fuzzy Clustering with Ensemble Classification techniques to improve the Customer Churn Prediction in Telecommunication Sector.- Chapter 4: Interval-valued complex fuzzy concept lattice and its granular decomposition.- Chapter 5: SBFP-growth: A Step to remove the bottleneck of FP-tree.- Chapter 6: Combining Multi-level Contexts of Superpixel using Convolutional Neural Networks to perform Natural Scene Labeling.- Chapter 7:  A fast Algorithm for Automatic Segmentation of Pancreas Histological Images for Glucose Intolerance Identification.- Chapter 8: Aptitude Question Paper Generator and Answer Verification System.- Chapter 9: Elephant Herding Algorithm for Clustering.- Chapter 10: Affinity Maturation of Homophones in Word-Level Speech Recognition.- Chapter 11: Fusion based Underwater Image Enhancement by Weight Map Techniques.- Chapter 12: IoT Enabled Ubiquitous Healthcare Data Acquisition and Monitoring System for Personal and Medical usage Powered by Cloud Application: An Architectural Overview.- Chapter 13: Analysis and Prediction of City Scale Transportation System Using XGBOOST Technique.- Chapter 14: Sensor Selection and Data Fusion Approach for IoT Applications.- Chapter 15: An overview of Hadoop Mapreduce, Spark and Scala-ble Graph Processing Architecture.- Chapter 16: Analyzing Social Trend towards Girl Child in India: A Machine Intelligence based Approach.

O autorze

Jugal K. Kalitais a professor at the Department of Computer Science at the University of Colorado, Colorado Springs, USA. He completed his MS and Ph.D. at the University of Pennsylvania, USA; M.Sc. at the University of Saskatchewan, Canada; and his B.Tech. at the Indian Institute of Technology Kharagpur, India. His areas of research include artificial intelligence, bioinformatics, information retrieval and computer security. He has published 200  journal/conference papers and 4 books.

Valentina E. Balas is currently a full professor at the Department of Automatics and Applied Software at the Faculty of Engineering, “AurelVlaicu” University of Arad, Romania. She holds a Ph.D. in Applied Electronics and Telecommunications from the Polytechnic University of Timisoara. Dr. Balas is the author of more than 250 research papers in refereed journals and international conferences. Her research interests are in intelligent systems, fuzzy control, soft computing, smart sensors, information fusion, modeling and simulation. She is the editor-in-chief of the International Journal of Advanced Intelligence Paradigms (IJAIP) and the International Journal of Computational Systems Engineering (IJCSysE), editorial board member of several national and international journals and is an expert evaluator for national and international projects. Dr. Balas is the director of the Intelligent Systems Research Centre at the AurelVlaicu University of Arad. From 2005–2016, she was general chair of the International Workshop Soft Computing and Applications (SOFA) held in Romania and Hungary. Dr. Balas has participated in numerous international conferences as organizer, honorary chair, session chair and member of steering, advisory or international program committees. She is a member of EUSFLAT, SIAM and a senior member of IEEE, member of TC – Fuzzy Systems (IEEE CIS), TC – Emergent Technologies (IEEE CIS), and of TC – Soft Computing (IEEE SMCS). Dr. Balas was vice-president (Awards) of the IFSA International Fuzzy Systems Association Council (2013–2015) and is a joint secretary of the Governing Council of the Forum for Interdisciplinary Mathematics (FIM) – A Multidisciplinary Academic Body, India.

 

Samarjeet Borah is currently working as Professor in the Department of Computer Applications, Sikkim Manipal University (SMU), Sikkim, India. Dr. Borah handles various academics, research and administrative activities. He is also involved in curriculum development activities, board of studies, doctoral research committee, IT infrastructure management etc. along with various administrative activities under SMU. Dr. Borah is involved with three funded projects in the capacity of Principal Investigator/Co-principal Investigator. The projects are sponsored by, AICTE (Govt. of India), DST-CSRI (Govt. of India) and Dr. TMA Pai Endowment Fund.  Out of which one is completed and two are undergoing. He is associated with IEEE, ACM (CSTA), IAENG and IACSIT. Dr. Borah organized various national and international conferences in SMU. Some of these events include ISRO Sponsored Training Programme on Remote Sensing & GIS, NCWBCB 2014, NER-WNLP 2014, IC3-2016, ICACCP 2017, IC3-2018 etc. Dr. Borah is involved with various journals of repute in the capacity of Editor/Guest Editor such as IJSE, IJHISI, IJGHPC, IJIM, IJVCSN, JISys, IJIPT etc. 

Dr. Ratika Pradhan has been a professor at the Department of Computer Science and Engineering, Sikkim Manipal Institute of Technology since 1999. She received her Ph.D. from Sikkim Manipal University (SMU) in 2011 and M.E. (CSE) from Jadavpur University in 2004. Her research interests include digital image processing, remote sensing and GIS. She has published 25 journal papers and 5 conference papers.

Blurb

This book presents high-quality papers from an international forum for research on computational approaches to learning. It includes current research and findings from various research labs, universities and institutions that may lead to development of marketable products. It also provides solid support for these findings in the form of empirical studies, theoretical analysis, or comparison to psychological phenomena. Further, it features work that shows how to apply learning methods to solve important application problems as well as how machine learning research is conducted. The book is divided into two main parts: Machine Learning Techniques, which covers machine learning-related research and findings; and, Data Analytics, which introduces recent developments in this domain. Additionally, the book includes work on data analytics using machine learning techniques.