Knowledge Discovery From Data Streams

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Knowledge Discovery From Data Streams

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Author : Joao Gama
language : en
Publisher: CRC Press
Release Date : 2010-05-25

Knowledge Discovery From Data Streams written by Joao Gama and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-05-25 with Business & Economics categories.

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 a coherent overview of state-of-the-art research in learning from data streams. The book covers the fundamentals that are imperative to understanding data streams and describes important applications, such as TCP/IP traffic, GPS data, sensor networks, and customer click streams. It also addresses several challenges of data mining in the future, when stream mining will be at the core of many applications. These challenges involve designing useful and efficient data mining solutions applicable to real-world problems. In the appendix, the author includes examples of publicly available software and online data sets. This practical, up-to-date book focuses on the new requirements of the next generation of data mining. Although the concepts presented in the text are mainly about data streams, they also are valid for different areas of machine learning and data mining.

Interactive Event Driven Knowledge Discovery From Data Streams

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Author : Laleh Jalali
language : en
Publisher:
Release Date : 2016

Interactive Event Driven Knowledge Discovery From Data Streams written by Laleh Jalali and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016 with categories.

With the proliferation of sensor data, a critical challenge is to interpret and extract knowledge from large-scale heterogeneous observational data. Most knowledge discovery frameworks relay on data mining techniques to extract interesting patterns. The problem of finding such patterns is NP-complete and the property of interestingness is not monotone since a pattern may be interesting, even if its subpatterns are not. In this dissertation a framework for interactive knowledge discovery from heterogeneous high-dimensional temporal data is presented. First, a high-level pattern formulation language is introduced. The language consists of an event model for fusing and abstracting data streams, a semi-interval time model for effectively representing temporal relations, and a set of expressive operators. Based on these operators, a visual and interactive framework is proposed which combines data-driven (bottom-up) and hypothesis-driven (top-down) analyses.This framework takes advantage of data-driven operators for pattern mining and investigating unknown unknowns to generate a basic model and derive a preliminary knowledge. It also uses domain expert knowledge to guide the process of revealing known unknowns. An expert can seed a hypothesis, based on prior knowledge or the knowledge derived from data-driven analysis, and grow it interactively using hypothesis-driven operators. In the context of the pattern mining component, novel time efficient algorithms are introduced which allow discovery of hidden event co-occurrences from multiple event streams. A prototype of the framework is implemented as a web based system which can be utilized as an effective tool for explanation and decision making in almost all disciplines. The applicability of this framework is evaluated in a healthcare application for asthma risk management and a human behavior understanding application, called Objective Self. These applications and experiments highlight the actionable knowledge that the framework can help uncover.

Knowledge Discovery From Data Streams

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Author :
language : en
Publisher:
Release Date : 2007

Knowledge Discovery From Data Streams written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with categories.

Fourth International Workshop On Knowledge Discovery From Data Streams

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Author :
language : en
Publisher:
Release Date : 2009

Fourth International Workshop On Knowledge Discovery From Data Streams written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009 with categories.

Proceedings Of The 4th International Workshop On Knowledge Discovery From Data Streams

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Author : Joao Gama
language : en
Publisher:
Release Date : 2006

Proceedings Of The 4th International Workshop On Knowledge Discovery From Data Streams written by Joao Gama and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with categories.

The Second International Workshop On Knowledge Discovery In Data Streams

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Author : João Gama
language : en
Publisher:
Release Date : 2005

The Second International Workshop On Knowledge Discovery In Data Streams written by João Gama and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005 with categories.

Data Streams

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Author : Charu C. Aggarwal
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-04-03

Data Streams written by Charu C. Aggarwal and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-04-03 with Computers categories.

This book primarily discusses issues related to the mining aspects of data streams and it is unique in its primary focus on the subject. This volume covers mining aspects of data streams comprehensively: each contributed chapter contains a survey on the topic, the key ideas in the field for that particular topic, and future research directions. The book is intended for a professional audience composed of researchers and practitioners in industry. This book is also appropriate for advanced-level students in computer science.

Learning From Data Streams

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Author : João Gama
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-09-20

Learning From Data Streams written by João Gama and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-09-20 with Computers categories.

Sensor networks consist of distributed autonomous devices that cooperatively monitor an environment. Sensors are equipped with capacities to store information in memory, process this information and communicate with their neighbors. Processing data streams generated from wireless sensor networks has raised new research challenges over the last few years due to the huge numbers of data streams to be managed continuously and at a very high rate. The book provides the reader with a comprehensive overview of stream data processing, including famous prototype implementations like the Nile system and the TinyOS operating system. The set of chapters covers the state-of-art in data stream mining approaches using clustering, predictive learning, and tensor analysis techniques, and applying them to applications in security, the natural sciences, and education. This research monograph delivers to researchers and graduate students the state of the art in data stream processing in sensor networks. The huge bibliography offers an excellent starting point for further reading and future research.

Advances In Knowledge Discovery And Data Mining

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Author : Usama M. Fayyad
language : en
Publisher:
Release Date : 1996

Advances In Knowledge Discovery And Data Mining written by Usama M. Fayyad and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996 with Computers categories.

Eight sections of this book span fundamental issues of knowledge discovery, classification and clustering, trend and deviation analysis, dependency derivation, integrated discovery systems, augumented database systems and application case studies. The appendices provide a list of terms used in the literature of the field of data mining and knowledge discovery in databases, and a list of online resources for the KDD researcher.

Knowledge Discovery From Heterogeneous Data Streams Using Fourier Spectrum Of Decision Trees

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Author : Byung-Hoon Park
language : en
Publisher:
Release Date : 2001

Knowledge Discovery From Heterogeneous Data Streams Using Fourier Spectrum Of Decision Trees written by Byung-Hoon Park and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001 with Data structures (Computer science) categories.