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Outlier detection for temporal data / (Record no. 562065)

000 -LEADER
fixed length control field 06872nam a2200757 i 4500
001 - CONTROL NUMBER
control field 6813100
003 - CONTROL NUMBER IDENTIFIER
control field IEEE
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20200413152914.0
006 - FIXED-LENGTH DATA ELEMENTS--ADDITIONAL MATERIAL CHARACTERISTICS
fixed length control field m eo d
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
fixed length control field cr cn |||m|||a
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 140422s2014 caua foab 000 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781627053761
Qualifying information ebook
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
Canceled/invalid ISBN 9781627053754
Qualifying information paperback
024 7# - OTHER STANDARD IDENTIFIER
Standard number or code 10.2200/S00573ED1V01Y201403DMK008
Source of number or code doi
035 ## - SYSTEM CONTROL NUMBER
System control number (CaBNVSL)swl00403313
035 ## - SYSTEM CONTROL NUMBER
System control number (OCoLC)877885434
040 ## - CATALOGING SOURCE
Original cataloging agency CaBNVSL
Language of cataloging eng
Description conventions rda
Transcribing agency CaBNVSL
Modifying agency CaBNVSL
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number QA276
Item number .G866 2014
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 519.5
Edition number 23
090 ## - LOCALLY ASSIGNED LC-TYPE CALL NUMBER (OCLC); LOCAL CALL NUMBER (RLIN)
Classification number (OCLC) (R) ; Classification number, CALL (RLIN) (NR)
Local cutter number (OCLC) ; Book number/undivided call number, CALL (RLIN) MoCl
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Gupta, Manish.,
Relator term author.
245 10 - TITLE STATEMENT
Title Outlier detection for temporal data /
Statement of responsibility, etc. Manish Gupta, Jing Gao, Charu Aggarwal, Jiawei Han.
264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Place of production, publication, distribution, manufacture San Rafael, California (1537 Fourth Street, San Rafael, CA 94901 USA) :
Name of producer, publisher, distributor, manufacturer Morgan & Claypool,
Date of production, publication, distribution, manufacture, or copyright notice 2014.
300 ## - PHYSICAL DESCRIPTION
Extent 1 PDF (xviii, 110 pages) :
Other physical details illustrations.
336 ## - CONTENT TYPE
Content type term text
Source rdacontent
337 ## - MEDIA TYPE
Media type term electronic
Source isbdmedia
338 ## - CARRIER TYPE
Carrier type term online resource
Source rdacarrier
490 1# - SERIES STATEMENT
Series statement Synthesis lectures on data mining and knowledge discovery,
International Standard Serial Number 2151-0075 ;
Volume/sequential designation # 8
538 ## - SYSTEM DETAILS NOTE
System details note Mode of access: World Wide Web.
538 ## - SYSTEM DETAILS NOTE
System details note System requirements: Adobe Acrobat Reader.
500 ## - GENERAL NOTE
General note Part of: Synthesis digital library of engineering and computer science.
500 ## - GENERAL NOTE
General note Series from website.
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc. note Includes bibliographical references (pages 91-108).
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note 1. Introduction and challenges -- 1.1 Temporal outlier examples -- 1.2 Different facets of temporal outlier analysis -- 1.3 Specific challenges for outlier detection for temporal data -- 1.4 Conclusions and summary --
505 8# - FORMATTED CONTENTS NOTE
Formatted contents note 2. Outlier detection for time series and data sequences -- 2.1 Outliers in time series databases -- 2.1.1 Direct detection of outlier time series -- 2.1.2 Window-based detection of outlier time series -- 2.1.3 Outlier subsequences in a test time series -- 2.1.4 Outlier points across multiple time series -- 2.2 Outliers within a given time series -- 2.2.1 Points as outliers -- 2.2.2 Subsequences as outliers -- 2.3 Conclusions and summary --
505 8# - FORMATTED CONTENTS NOTE
Formatted contents note 3. Outlier detection for data streams -- 3.1 Evolving prediction models -- 3.1.1 Online sequential discounting -- 3.1.2 Dynamic cluster maintenance -- 3.1.3 Dynamic Bayesian networks (DBNS) -- 3.2 Distance-based outliers for sliding windows -- 3.2.1 Distance-based global outliers -- 3.2.2 Distance-based local outliers -- 3.3 Outliers in high-dimensional data streams -- 3.4 Detecting aggregate windows of change -- 3.5 Supervised methods for streaming outlier detection -- 3.6 Conclusions and summary --
505 8# - FORMATTED CONTENTS NOTE
Formatted contents note 4. Outlier detection for distributed data streams -- 4.1 Examples and challenges -- 4.2 Sharing data points -- 4.3 Sharing local outliers and other data points -- 4.4 Sharing model parameters -- 4.5 Sharing local outliers and data distributions -- 4.6 Vertically partitioned distributed data -- 4.7 Conclusions and summary --
505 8# - FORMATTED CONTENTS NOTE
Formatted contents note 5. Outlier detection for spatio-temporal data -- 5.1 Spatio-temporal outliers (ST-outliers) -- 5.1.1 Density-based outlier detection -- 5.1.2 Outlier detection using spatial scaling -- 5.1.3 Outlier detection using Voronoi diagrams -- 5.2 Spatio-temporal outlier solids -- 5.2.1 Using Kulldorff scan statistic -- 5.2.2 Using image processing -- 5.3 Trajectory outliers -- 5.3.1 Distance between trajectories -- 5.3.2 Direction and density of trajectories -- 5.3.3 Historical similarity -- 5.3.4 Trajectory motifs -- 5.4 Conclusions and summary --
505 8# - FORMATTED CONTENTS NOTE
Formatted contents note 6. Outlier detection for temporal network data -- 6.1 Outlier graphs from graph time series -- 6.1.1 Weight independent metrics -- 6.1.2 Metrics using edge weights -- 6.1.3 Metrics using vertex weights -- 6.1.4 Scan statistics -- 6.2 Multi-level outlier detection from graph snapshots -- 6.2.1 Elbows, broken correlations, prolonged spikes, and lightweight stars -- 6.2.2 Outlier node pairs -- 6.3 Community-based outlier detection algorithms -- 6.3.1 Community outliers using community change patterns -- 6.3.2 Change detection using minimum description length -- 6.3.3 Community outliers using evolutionary clustering -- 6.4 Online graph outlier detection algorithms -- 6.4.1 Spectral methods -- 6.4.2 Structural outlier detection -- 6.5 Conclusions and summary --
505 8# - FORMATTED CONTENTS NOTE
Formatted contents note 7. Applications of outlier detection for temporal data -- 7.1 Temporal outliers in environmental sensor data -- 7.2 Temporal outliers in industrial sensor data -- 7.3 Temporal outliers in surveillance and trajectory data -- 7.4 Temporal outliers in computer networks data -- 7.5 Temporal outliers in biological data -- 7.6 Temporal outliers in astronomy data -- 7.7 Temporal outliers in web data -- 7.8 Temporal outliers in information network data -- 7.9 Temporal outliers in economics time series data -- 7.10 Conclusions and summary --
505 8# - FORMATTED CONTENTS NOTE
Formatted contents note 8. Conclusions and research directions -- Bibliography -- Authors' biographies.
506 1# - RESTRICTIONS ON ACCESS NOTE
Terms governing access Abstract freely available; full-text restricted to subscribers or individual document purchasers.
510 0# - CITATION/REFERENCES NOTE
Name of source Compendex
510 0# - CITATION/REFERENCES NOTE
Name of source INSPEC
510 0# - CITATION/REFERENCES NOTE
Name of source Google scholar
510 0# - CITATION/REFERENCES NOTE
Name of source Google book search
520 3# - SUMMARY, ETC.
Summary, etc. Outlier (or anomaly) detection is a very broad field which has been studied in the context of a large number of research areas like statistics, data mining, sensor networks, environmental science, distributed systems, spatio-temporal mining, etc. Initial research in outlier detection focused on time series-based outliers (in statistics). Since then, outlier detection has been studied on a large variety of data types including high-dimensional data, uncertain data, stream data, network data, time series data, spatial data, and spatio-temporal data. While there have been many tutorials and surveys for general outlier detection, we focus on outlier detection for temporal data in this book.
530 ## - ADDITIONAL PHYSICAL FORM AVAILABLE NOTE
Additional physical form available note Also available in print.
588 ## - SOURCE OF DESCRIPTION NOTE
Source of description note Title from PDF title page (viewed on April 22, 2014).
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Outliers (Statistics)
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Temporal databases.
653 ## - INDEX TERM--UNCONTROLLED
Uncontrolled term temporal outlier detection
653 ## - INDEX TERM--UNCONTROLLED
Uncontrolled term time series data
653 ## - INDEX TERM--UNCONTROLLED
Uncontrolled term data streams
653 ## - INDEX TERM--UNCONTROLLED
Uncontrolled term distributed data streams
653 ## - INDEX TERM--UNCONTROLLED
Uncontrolled term temporal networks
653 ## - INDEX TERM--UNCONTROLLED
Uncontrolled term spatiotemporal outliers
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Gao, Jing.,
Relator term author.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Aggarwal, Charu C.,
Relator term author.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Han, Jiawei.,
Relator term author.
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Relationship information Print version:
International Standard Book Number 9781627053754
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
Uniform title Synthesis digital library of engineering and computer science.
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
Uniform title Synthesis lectures on data mining and knowledge discovery ;
Volume/sequential designation # 8.
International Standard Serial Number 2151-0075
856 42 - ELECTRONIC LOCATION AND ACCESS
Materials specified Abstract with links to resource
Uniform Resource Identifier http://ieeexplore.ieee.org/servlet/opac?bknumber=6813100
856 40 - ELECTRONIC LOCATION AND ACCESS
Materials specified Abstract with links to full text
Uniform Resource Identifier http://dx.doi.org/10.2200/S00573ED1V01Y201403DMK008
Holdings
Withdrawn status Lost status Damaged status Not for loan Permanent Location Current Location Date acquired Barcode Date last seen Price effective from Koha item type
        PK Kelkar Library, IIT Kanpur PK Kelkar Library, IIT Kanpur 2020-04-13 EBKE565 2020-04-13 2020-04-13 E books

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