Discovering Unusual And Non Trivial Patterns In Massive Time Series Databases
DOWNLOAD
Download Discovering Unusual And Non Trivial Patterns In Massive Time Series Databases PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Discovering Unusual And Non Trivial Patterns In Massive Time Series Databases book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Discovering Unusual And Non Trivial Patterns In Massive Time Series Databases
DOWNLOAD
Author : Jessica Hung-Fan Lin
language : en
Publisher:
Release Date : 2005
Discovering Unusual And Non Trivial Patterns In Massive Time Series Databases written by Jessica Hung-Fan Lin and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005 with Cluster analysis categories.
Temporal Data Mining
DOWNLOAD
Author : Theophano Mitsa
language : en
Publisher: CRC Press
Release Date : 2010-03-10
Temporal Data Mining written by Theophano Mitsa and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-03-10 with Computers categories.
Temporal data mining deals with the harvesting of useful information from temporal data. New initiatives in health care and business organizations have increased the importance of temporal information in data today. From basic data mining concepts to state-of-the-art advances, Temporal Data Mining covers the theory of this subject as well as its application in a variety of fields. It discusses the incorporation of temporality in databases as well as temporal data representation, similarity computation, data classification, clustering, pattern discovery, and prediction. The book also explores the use of temporal data mining in medicine and biomedical informatics, business and industrial applications, web usage mining, and spatiotemporal data mining. Along with various state-of-the-art algorithms, each chapter includes detailed references and short descriptions of relevant algorithms and techniques described in other references. In the appendices, the author explains how data mining fits the overall goal of an organization and how these data can be interpreted for the purpose of characterizing a population. She also provides programs written in the Java language that implement some of the algorithms presented in the first chapter. Check out the author's blog at http://theophanomitsa.wordpress.com/
Efficient Pattern Discovery In Massive Time Series Databases
DOWNLOAD
Author : Li Wei
language : en
Publisher:
Release Date : 2006
Efficient Pattern Discovery In Massive Time Series Databases written by Li Wei and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with Data mining categories.
Dissertation Abstracts International
DOWNLOAD
Author :
language : en
Publisher:
Release Date : 2006
Dissertation Abstracts International written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with Dissertations, Academic categories.
Data Mining In Time Series Databases
DOWNLOAD
Author : Mark Last
language : en
Publisher: World Scientific
Release Date : 2004
Data Mining In Time Series Databases written by Mark Last and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with Mathematics categories.
Adding the time dimension to real-world databases produces Time Series Databases (TSDB) and introduces new aspects and difficulties to data mining and knowledge discovery. This book covers the state-of-the-art methodology for mining time series databases. The novel data mining methods presented in the book include techniques for efficient segmentation, indexing, and classification of noisy and dynamic time series. A graph-based method for anomaly detection in time series is described and the book also studies the implications of a novel and potentially useful representation of time series as strings. The problem of detecting changes in data mining models that are induced from temporal databases is additionally discussed. Contents: A Survey of Recent Methods for Efficient Retrieval of Similar Time Sequences (H M Lie); Indexing of Compressed Time Series (E Fink & K Pratt); Boosting Interval-Based Literal: Variable Length and Early Classification (J J Rodriguez Diez); Segmenting Time Series: A Survey and Novel Approach (E Keogh et al.); Indexing Similar Time Series under Conditions of Noise (M Vlachos et al.); Classification of Events in Time Series of Graphs (H Bunke & M Kraetzl); Median Strings--A Review (X Jiang et al.); Change Detection in Classfication Models of Data Mining (G Zeira et al.). Readership: Graduate students, reseachers and practitioners in the fields of data mining, machine learning, databases and statistics.
Eceg2016 Proceedings Of 16th European Conference On E Government Eceg 2016
DOWNLOAD
Author : Mitja Decman
language : en
Publisher: Academic Conferences and publishing limited
Release Date : 2016-06-02
Eceg2016 Proceedings Of 16th European Conference On E Government Eceg 2016 written by Mitja Decman and has been published by Academic Conferences and publishing limited this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-06-02 with Business & Economics categories.
High Performance Discovery In Time Series
DOWNLOAD
Author : Donna Ryan
language : en
Publisher:
Release Date : 2014-01-15
High Performance Discovery In Time Series written by Donna Ryan and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-01-15 with categories.
Mining Of Massive Datasets
DOWNLOAD
Author : Jure Leskovec
language : en
Publisher: Cambridge University Press
Release Date : 2014-11-13
Mining Of Massive Datasets written by Jure Leskovec and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-11-13 with Computers categories.
Now in its second edition, this book focuses on practical algorithms for mining data from even the largest datasets.
Proceedings Of The Seventh Siam International Conference On Data Mining
DOWNLOAD
Author : Chid Apte
language : en
Publisher: Proceedings in Applied Mathema
Release Date : 2007
Proceedings Of The Seventh Siam International Conference On Data Mining written by Chid Apte and has been published by Proceedings in Applied Mathema this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with Computers categories.
The Seventh SIAM International Conference on Data Mining (SDM 2007) continues a series of conferences whose focus is the theory and application of data mining to complex datasets in science, engineering, biomedicine, and the social sciences. These datasets challenge our abilities to analyze them because they are large and often noisy. Sophisticated, highperformance, and principled analysis techniques and algorithms, based on sound statistical foundations, are required. Visualization is often critically important; tuning for performance is a significant challenge; and the appropriate levels of abstraction to allow end-users to exploit sophisticated techniques and understand clearly both the constraints and interpretation of results are still something of an open question.
Floods In A Changing Climate
DOWNLOAD
Author : Ramesh S. V. Teegavarapu
language : en
Publisher: Cambridge University Press
Release Date : 2012-11-22
Floods In A Changing Climate written by Ramesh S. V. Teegavarapu and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-11-22 with Science categories.
Measurement, analysis and modeling of extreme precipitation events linked to floods is vital in understanding changing climate impacts and variability. This book provides methods for assessment of the trends in these events and their impacts. It also provides a basis to develop procedures and guidelines for climate-adaptive hydrologic engineering. Academic researchers in the fields of hydrology, climate change, meteorology, environmental policy and risk assessment, and professionals and policy-makers working in hazard mitigation, water resources engineering and climate adaptation will find this an invaluable resource. This volume is the first in a collection of four books on flood disaster management theory and practice within the context of anthropogenic climate change. The others are: Floods in a Changing Climate: Hydrological Modeling by P. P. Mujumdar and D. Nagesh Kumar, Floods in a Changing Climate: Inundation Modeling by Giuliano Di Baldassarre and Floods in a Changing Climate: Risk Management by Slodoban Simonović.