Predictive Analysis on Large Data for Actionable Knowledge: Emerging Research and Opportunities

Predictive Analysis on Large Data for Actionable Knowledge: Emerging Research and Opportunities

Muhammad Usman (Shaheed Zulfikar Ali Bhutto Institute of Science and Technology, Pakistan) and M. Usman (Pakistan Scientific and Technological Information Center (PASTIC), Pakistan)
Release Date: January, 2018|Copyright: © 2018 |Pages: 177
ISBN13: 9781522550297|ISBN10: 1522550291|EISBN13: 9781522550303|DOI: 10.4018/978-1-5225-5029-7

Description

Data analysis forms the basis of many modes of research ranging from scientific discoveries to governmental findings. With the advent of machine intelligence and neural networks, extracting and modeling, approaching data has been unimpeachably altered. These changes, seemingly small, affect the way societies organize themselves, deliver services, or interact with each other.

Predictive Analysis on Large Data for Actionable Knowledge: Emerging Research and Opportunities provides emerging information on extraction and prediction patterns in data mining along with knowledge discovery. While highlighting the current issues in data extraction, readers will learn new methodologies comprising of different algorithms that automate the multidimensional schema that remove the manual processes. This book is a vital resource for researchers, academics, and those seeking new information on data mining techniques and trends.

Topics Covered

The many academic areas covered in this publication include, but are not limited to:

  • Association Rule Mining
  • Data Mining
  • Exploratory Pattern Recognition
  • General Hierarchical Clusters
  • Hybrid Techniques
  • Knowledge Discovery
  • Machine Learning
  • Pattern Extraction
  • Prediction Algorithms
  • Principle Component Analysis
  • Visualization Techniques

Table of Contents and List of Contributors

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Author(s)/Editor(s) Biography

Dr. Muhammad Usman has completed PhD in Computer & Information Sciences from Auckland University of Technology, New Zealand. He is currently an Associate Professor and Head of Computer Science Department at Shaheed Zulfikar Ali Bhutto Institute of Science and Technology (SZABIST), Islamabad, Pakistan. His research interests include Data Mining, Data Warehousing, Machine Learning, Business Intelligence and Knowledge discovery. He is currently researching in the novel methods and techniques for the seamless integration of Data Mining and Data Warehousing technologies. He has published in international journals and conference proceedings, and he has served as reviewer for a number of premier journals and conferences.