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  • Conference proceedings
  • © 2018

Advances in Machine Learning and Data Science

Recent Achievements and Research Directives

  • Presents studies involving innovative combination of machine learning and data science
  • Presents latest ideas and techniques in the field of data mining
  • Serves as a good reference material for future work

Part of the book series: Advances in Intelligent Systems and Computing (AISC, volume 705)

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Table of contents (39 papers)

  1. Front Matter

    Pages i-xii
  2. Accelerating Airline Delay Prediction-Based P-CUDA Computing Environment

    • Dharavath Ramesh, Neeraj Patidar, Teja Vunnam, Gaurav Kumar
    Pages 9-20
  3. IDPC-XML: Integrated Data Provenance Capture in XML

    • Dharavath Ramesh, Himangshu Biswas, Vijay Kumar Vallamdas
    Pages 21-32
  4. Predicting High Blood Pressure Using Decision Tree-Based Algorithm

    • Satyanarayana Nimmala, Y. Ramadevi, Srinivas Naik Nenavath, Ramalingaswamy Cheruku
    Pages 53-60
  5. Image Manipulation Detection Using Harris Corner and ANMS

    • Choudhary Shyam Prakash, Sushila Maheshkar, Vikas Maheshkar
    Pages 81-93
  6. Spatial Co-location Pattern Mining Using Delaunay Triangulation

    • G. Kiran Kumar, Ilaiah Kavati, Koppula Srinivas Rao, Ramalingaswamy Cheruku
    Pages 95-102
  7. Review on RBFNN Design Approaches: A Case Study on Diabetes Data

    • Ramalingaswamy Cheruku, Diwakar Tripathi, Y. Narasimha Reddy, Sathya Prakash Racharla
    Pages 103-112
  8. Keyphrase and Relation Extraction from Scientific Publications

    • R. C. Anju, Sree Harsha Ramesh, P. C. Rafeeque
    Pages 113-120
  9. Mixing and Entrainment Characteristics of Jet Control with Crosswire

    • S. Manigandan, K. Vijayaraja, G. Durga Revanth, A. V. S. C. Anudeep
    Pages 121-128
  10. GCV-Based Regularized Extreme Learning Machine for Facial Expression Recognition

    • Shraddha Naik, Ravi Prasad K. Jagannath
    Pages 129-138
  11. Game Theory-Based Defense Mechanisms of Cyber Warfare

    • Monica Ravishankar, D. Vijay Rao, C. R. S. Kumar
    Pages 149-152
  12. Segmentation Techniques for Computer-Aided Diagnosis of Glaucoma: A Review

    • Sumaiya Pathan, Preetham Kumar, Radhika M. Pai
    Pages 163-173

About this book

The Volume of “Advances in Machine Learning and Data Science - Recent Achievements and Research Directives” constitutes the proceedings of First International Conference on Latest Advances in Machine Learning and Data Science (LAMDA 2017). The 37 regular papers presented in this volume were carefully reviewed and selected from 123 submissions.

These days we find many computer programs that exhibit various useful learning methods and commercial applications. Goal of machine learning is to develop computer programs that can learn from experience. Machine learning involves knowledge from various disciplines like, statistics, information theory, artificial intelligence, computational complexity, cognitive science and biology. For problems like handwriting recognition, algorithms that are based on machine learning out perform all other approaches. Both machine learning and data science are interrelated. Data science is an umbrella term to be used for techniques that cleandata and extract useful information from data. In field of data science, machine learning algorithms are used frequently to identify valuable knowledge from commercial databases containing records of different industries, financial transactions, medical records, etc.

The main objective of this book is to provide an overview on latest advancements in the field of machine learning and data science, with solutions to problems in field of image, video, data and graph processing, pattern recognition, data structuring, data clustering, pattern mining, association rule based approaches, feature extraction techniques, neural networks, bio inspired learning and various machine learning algorithms. 


Editors and Affiliations

  • Department of Computer Science and Engineering, National Institute of Technology Goa, Goa, India

    Damodar Reddy Edla, Venkatanareshbabu K.

  • Department of Mathematics and Computing Science, Saint Mary’s University, Halifax, Canada

    Pawan Lingras

About the editors

Damodar Reddy Edla is Assistant Professor and Head in Department of Computer Science & Engineering, National Institute of Technology Goa, India. His research interests include Data Mining and Wireless Sensor Networks. He has completed his doctorate from Indian School of Mines, Dhanbad, India, in 2013. He has published more than 35 research papers in national and international journals and conference proceedings. He is editorial board member of 5 International journals.    

Pawan Lingras is a graduate of IIT Bombay with graduate studies from University of Regina. He is currently a Professor and Director of Computing and Data Analytics at Saint Marys University, Halifax. He is also internationally active having served as a visiting professor at Munich University of Applied Sciences, IIT Gandhinagar, as a research supervisor at Institut Superieur de Gestion de Tunis, as a Scholar-in-Residence, and as a Shastri Indo-Canadian scholar. He has deliveredmore than 35 invited talks at various institutions around the world. He has authored more than 200 research papers in various international journals and conferences.  He has also co-authored three textbooks, and co-edited two books and eight volumes of research papers. His academic collaborations/co-authors include academics from Canada, Chile, China, Germany, India, Poland, Tunisia, U.K. and USA. His areas of interests include artificial intelligence, information retrieval, data mining, web intelligence, and intelligent transportation systems. He has served as the general co-chair, program co-chair, review committee chair, program committee member, and reviewer for various international conferences on artificial intelligence and data mining. He is also on editorial boards of a number of international journals. His research has been supported by Natural Science and Engineering Research Council (NSERC) of Canada for twenty-five years, as well as other funding agencies including NRC-IRAP and MITACS. He also served on the NSERC’s Computer Science peer review committee. He has been awarded an Alumni association excellence in teaching award, Student union’s faculty of science teaching award, and President’s award for excellence in research at Saint Mary’s University. 

Venkatanareshbabu Kuppili is with the Machine Learning Group, Department of Computer Science and Engineering, National Institute of Technology Goa, India, where he is currently an Assistant Professor. He obtained doctoral degree from Indian Institute of Technology Delhi in 2014. He was with Evalueserve Pvt. Ltd., as a Senior Research Associate in 2009. He has been a Visiting Scientist with the Global Medical Technologies, California in 2017. He has been the Principal Investigator of many sponsored research and consultancy research projects in the field of neural networks and machine learning. He is also actively involved in teaching and project coordination for the Graduate and Post Graduate Program in Computer Science and Engineering Department at the National Institute of Technology Goa. He has authored a number of research papers published in reputed international journals in the area of neural networks, classification, and clustering.

 


Bibliographic Information

Buy it now

Buying options

eBook USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access