Mining Spatiotemporal Information Systems: Unlocking the Power of Location and Time in Data Analysis
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Mining Spatio Temporal Information Systems: A Comprehensive Guide for Extracting Knowledge and Insights from Spatio Temporal Data
In today's data-driven world, organizations are increasingly recognizing the importance of extracting valuable insights from their data, including the spatiotemporal aspects of that data. Spatiotemporal data, which combines spatial and temporal information, offers a richer understanding of real-world events and patterns.
5 out of 5
Language | : | English |
File size | : | 3161 KB |
Text-to-Speech | : | Enabled |
Word Wise | : | Enabled |
Print length | : | 180 pages |
Mining Spatiotemporal Information Systems provides a comprehensive guide to the latest techniques and algorithms for extracting knowledge and insights from spatiotemporal data. Written by leading experts in the field, this book covers a wide range of topics, from fundamental concepts to advanced applications.
Key Features:
- Covers a wide range of topics, from fundamental concepts to advanced applications
- Provides a comprehensive overview of the latest techniques and algorithms for extracting knowledge and insights from spatiotemporal data
- Written by leading experts in the field
- Includes numerous case studies and examples to illustrate the practical applications of spatiotemporal data mining
This book is an essential resource for anyone who wants to learn about the latest advances in spatiotemporal data mining. It is also a valuable reference for researchers and practitioners who are working with spatiotemporal data.
Table of Contents
- to Spatiotemporal Data Mining
- Basic Concepts of Spatiotemporal Data Mining
- Data Acquisition and Preprocessing
- Spatial Data Mining
- Temporal Data Mining
- Spatiotemporal Data Mining
- Applications of Spatiotemporal Data Mining
- Future Directions in Spatiotemporal Data Mining
Author Biographies
Dr. Jiawei Han is a University Distinguished Professor and the director of the Data Mining and Machine Learning Lab at the University of Illinois at Urbana-Champaign. He is a leading researcher in the field of data mining and has published over 600 papers and several books on the topic.
Dr. Micheline Kamber is a University Distinguished Professor and the director of the Center for Advanced Data Mining and Applications at Simon Fraser University. She is a leading researcher in the field of data mining and has published over 300 papers and several books on the topic.
Free Download Your Copy Today!
Mining Spatiotemporal Information Systems is available now from Springer. To Free Download your copy, please visit the Springer website or your local bookstore.
5 out of 5
Language | : | English |
File size | : | 3161 KB |
Text-to-Speech | : | Enabled |
Word Wise | : | Enabled |
Print length | : | 180 pages |
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5 out of 5
Language | : | English |
File size | : | 3161 KB |
Text-to-Speech | : | Enabled |
Word Wise | : | Enabled |
Print length | : | 180 pages |