Knowledge Discovery from Sensor Data

Knowledge Discovery from Sensor Data
Author: Mohamed Medhat Gaber
Publisher: Springer
Total Pages: 235
Release: 2010-04-07
Genre: Computers
ISBN: 3642125190

This book contains thoroughly refereed extended papers from the Second International Workshop on Knowledge Discovery from Sensor Data, Sensor-KDD 2008, held in Las Vegas, NV, USA, in August 2008. The 12 revised papers presented together with an invited paper were carefully reviewed and selected from numerous submissions. The papers feature important aspects of knowledge discovery from sensor data, e.g., data mining for diagnostic debugging; incremental histogram distribution for change detection; situation-aware adaptive visualization; WiFi mining; mobile sensor data mining; incremental anomaly detection; and spatiotemporal neighborhood discovery for sensor data.

Knowledge Discovery from Sensor Data

Knowledge Discovery from Sensor Data
Author: Mohamed Medhat Gaber
Publisher: Springer Science & Business Media
Total Pages: 235
Release: 2010-04-14
Genre: Computers
ISBN: 3642125182

This book contains thoroughly refereed extended papers from the Second International Workshop on Knowledge Discovery from Sensor Data, Sensor-KDD 2008, held in Las Vegas, NV, USA, in August 2008. The 12 revised papers presented together with an invited paper were carefully reviewed and selected from numerous submissions. The papers feature important aspects of knowledge discovery from sensor data, e.g., data mining for diagnostic debugging; incremental histogram distribution for change detection; situation-aware adaptive visualization; WiFi mining; mobile sensor data mining; incremental anomaly detection; and spatiotemporal neighborhood discovery for sensor data.

Knowledge Discovery from Data Streams

Knowledge Discovery from Data Streams
Author: Joao Gama
Publisher: CRC Press
Total Pages: 256
Release: 2010-05-25
Genre: Business & Economics
ISBN: 1439826129

Since the beginning of the Internet age and the increased use of ubiquitous computing devices, the large volume and continuous flow of distributed data have imposed new constraints on the design of learning algorithms. Exploring how to extract knowledge structures from evolving and time-changing data, Knowledge Discovery from Data Streams presents

Managing and Mining Sensor Data

Managing and Mining Sensor Data
Author: Charu C. Aggarwal
Publisher: Springer Science & Business Media
Total Pages: 547
Release: 2013-01-15
Genre: Computers
ISBN: 1461463092

Advances in hardware technology have lead to an ability to collect data with the use of a variety of sensor technologies. In particular sensor notes have become cheaper and more efficient, and have even been integrated into day-to-day devices of use, such as mobile phones. This has lead to a much larger scale of applicability and mining of sensor data sets. The human-centric aspect of sensor data has created tremendous opportunities in integrating social aspects of sensor data collection into the mining process. Managing and Mining Sensor Data is a contributed volume by prominent leaders in this field, targeting advanced-level students in computer science as a secondary text book or reference. Practitioners and researchers working in this field will also find this book useful.

Big Data Analytics and Knowledge Discovery

Big Data Analytics and Knowledge Discovery
Author: Sanjay Madria
Publisher: Springer
Total Pages: 419
Release: 2015-08-09
Genre: Computers
ISBN: 3319227297

This book constitutes the refereed proceedings of the 17th International Conference on Data Warehousing and Knowledge Discovery, DaWaK 2015, held in Valencia, Spain, September 2015. The 31 revised full papers presented were carefully reviewed and selected from 90 submissions. The papers are organized in topical sections similarity measure and clustering; data mining; social computing; heterogeneos networks and data; data warehouses; stream processing; applications of big data analysis; and big data.

Data Mining and Knowledge Discovery for Process Monitoring and Control

Data Mining and Knowledge Discovery for Process Monitoring and Control
Author: Xue Z. Wang
Publisher: Springer Science & Business Media
Total Pages: 263
Release: 2012-12-06
Genre: Computers
ISBN: 1447104218

Modern computer-based control systems are able to collect a large amount of information, display it to operators and store it in databases but the interpretation of the data and the subsequent decision making relies mainly on operators with little computer support. This book introduces developments in automatic analysis and interpretation of process-operational data both in real-time and over the operational history, and describes new concepts and methodologies for developing intelligent, state space-based systems for process monitoring, control and diagnosis. The book brings together new methods and algorithms from process monitoring and control, data mining and knowledge discovery, artificial intelligence, pattern recognition, and causal relationship discovery, as well as signal processing. It also provides a framework for integrating plant operators and supervisors into the design of process monitoring and control systems.

Machine Learning Techniques for Improved Business Analytics

Machine Learning Techniques for Improved Business Analytics
Author: G., Dileep Kumar
Publisher: IGI Global
Total Pages: 300
Release: 2018-07-06
Genre: Business & Economics
ISBN: 1522535357

Analytical tools and algorithms are essential in business data and information systems. Efficient economic and financial forecasting in machine learning techniques increases gains while reducing risks. Providing research on predictive models with high accuracy, stability, and ease of interpretation is important in improving data preparation, analysis, and implementation processes in business organizations. Machine Learning Techniques for Improved Business Analytics is a collection of innovative research on the methods and applications of artificial intelligence in strategic business decisions and management. Featuring coverage on a broad range of topics such as data mining, portfolio optimization, and social network analysis, this book is ideally designed for business managers and practitioners, upper-level business students, and researchers seeking current research on large-scale information control and evaluation technologies that exceed the functionality of conventional data processing techniques.

Data Warehousing and Knowledge Discovery

Data Warehousing and Knowledge Discovery
Author: Alfredo Cuzzocrea
Publisher: Springer
Total Pages: 510
Release: 2011-08-19
Genre: Computers
ISBN: 3642235441

This book constitutes the refereed proceedings of the 13th International Conference on Data Warehousing and Knowledge Discovery, DaWak 2011 held in Toulouse, France in August/September 2011. The 37 revised full papers presented were carefully reviewed and selected from 119 submissions. The papers are organized in topical sections on physical and conceptual data warehouse models, data warehousing design methodologies and tools, data warehouse performance and optimization, pattern mining, matrix-based mining techniques and stream, sensor and time-series mining.