國立虎尾科技大學 |

Advanced Analytics and Learning on Temporal Data = 4th ECML PKDD Workshop, AALTD 2019, Würzburg, Germany, September 20, 2019, Revised Selected Papers /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Advanced Analytics and Learning on Temporal Data/ edited by Vincent Lemaire, Simon Malinowski, Anthony Bagnall, Alexis Bondu, Thomas Guyet, Romain Tavenard.
Reminder of title:	4th ECML PKDD Workshop, AALTD 2019, Würzburg, Germany, September 20, 2019, Revised Selected Papers /
other author:	Lemaire, Vincent.
Description:	X, 229 p. 109 illus., 90 illus. in color.online resource. :
Contained By:	Springer Nature eBook
Subject:	Artificial intelligence. -
Online resource:	https://doi.org/10.1007/978-3-030-39098-3
ISBN:	9783030390983

Advanced Analytics and Learning on Temporal Data = 4th ECML PKDD Workshop, AALTD 2019, Würzburg, Germany, September 20, 2019, Revised Selected Papers /
Advanced Analytics and Learning on Temporal Data4th ECML PKDD Workshop, AALTD 2019, Würzburg, Germany, September 20, 2019, Revised Selected Papers /[electronic resource] :edited by Vincent Lemaire, Simon Malinowski, Anthony Bagnall, Alexis Bondu, Thomas Guyet, Romain Tavenard. - 1st ed. 2020. - X, 229 p. 109 illus., 90 illus. in color.online resource. - Lecture Notes in Artificial Intelligence ;11986. - Lecture Notes in Artificial Intelligence ;9285.

Robust Functional Regression for Outlier Detection -- Transform Learning Based Function Approximation for Regression and Forecasting -- Proactive Fiber Break Detection based on Quaternion Time Series and Automatic Variable Selection from Relational Data -- A fully automated periodicity detection in time series -- Conditional Forecasting of Water Level Time Series with RNNs -- Challenges and Limitations in Clustering Blood Donor Hemoglobin Trajectories -- Localized Random Shapelets -- Feature-Based Gait Pattern Classification for a Robotic Walking Frame -- How to detect novelty in textual data streams? A comparative study of existing methods -- Seq2VAR: multivariate time series representation with relational neural networks and linear autoregressive model -- Modelling Patient Sequences for Rare Disease Detection with Semi-supervised Generative Adversarial Nets -- Extended Kalman Filter for Large Scale Vessels Trajectory Tracking in Distributed Stream Processing Systems -- Unsupervised Anomaly Detection in Multivariate Spatio-Temporal Datasets using Deep Learning -- Learning Stochastic Dynamical Systems via Bridge Sampling -- Quantifying Quality of Actions Using Wearable Sensor -- An Initial Study on Adapting DTW at Individual Query for Electrocardiogram Analysis.

This book constitutes the refereed proceedings of the 4th ECML PKDD Workshop on Advanced Analytics and Learning on Temporal Data, AALTD 2019, held in Würzburg, Germany, in September 2019. The 7 full papers presented together with 9 poster papers were carefully reviewed and selected from 31 submissions. The papers cover topics such as temporal data clustering; classification of univariate and multivariate time series; early classification of temporal data; deep learning and learning representations for temporal data; modeling temporal dependencies; advanced forecasting and prediction models; space-temporal statistical analysis; functional data analysis methods; temporal data streams; interpretable time-series analysis methods; dimensionality reduction, sparsity, algorithmic complexity and big data challenge; and bio-informatics, medical, energy consumption, on temporal data. .

ISBN: 9783030390983

Standard No.: 10.1007/978-3-030-39098-3doiSubjects--Topical Terms:

559380
Artificial intelligence.

LC Class. No.: Q334-342

Dewey Class. No.: 006.3

Advanced Analytics and Learning on Temporal Data = 4th ECML PKDD Workshop, AALTD 2019, Würzburg, Germany, September 20, 2019, Revised Selected Papers /
LDR:03740nam a22004095i 4500 001 1019338
003 DE-He213
005 20201110131125.0
007 cr nn 008mamaa
008 210318s2020 gw | s |||| 0|eng d
020 $a 9783030390983 $9 978-3-030-39098-3
024 7 $a 10.1007/978-3-030-39098-3 $2 doi
035 $a 978-3-030-39098-3
050 4 $a Q334-342
072 7 $a UYQ $2 bicssc
072 7 $a COM004000 $2 bisacsh
072 7 $a UYQ $2 thema
082 0 4 $a 006.3 $2 23
245 1 0 $a Advanced Analytics and Learning on Temporal Data $h [electronic resource] : $b 4th ECML PKDD Workshop, AALTD 2019, Würzburg, Germany, September 20, 2019, Revised Selected Papers / $c edited by Vincent Lemaire, Simon Malinowski, Anthony Bagnall, Alexis Bondu, Thomas Guyet, Romain Tavenard.
250 $a 1st ed. 2020.
264 1 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2020.
300 $a X, 229 p. 109 illus., 90 illus. in color. $b online resource.
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
347 $a text file $b PDF $2 rda
490 1 $a Lecture Notes in Artificial Intelligence ; $v 11986
505 0 $a Robust Functional Regression for Outlier Detection -- Transform Learning Based Function Approximation for Regression and Forecasting -- Proactive Fiber Break Detection based on Quaternion Time Series and Automatic Variable Selection from Relational Data -- A fully automated periodicity detection in time series -- Conditional Forecasting of Water Level Time Series with RNNs -- Challenges and Limitations in Clustering Blood Donor Hemoglobin Trajectories -- Localized Random Shapelets -- Feature-Based Gait Pattern Classification for a Robotic Walking Frame -- How to detect novelty in textual data streams? A comparative study of existing methods -- Seq2VAR: multivariate time series representation with relational neural networks and linear autoregressive model -- Modelling Patient Sequences for Rare Disease Detection with Semi-supervised Generative Adversarial Nets -- Extended Kalman Filter for Large Scale Vessels Trajectory Tracking in Distributed Stream Processing Systems -- Unsupervised Anomaly Detection in Multivariate Spatio-Temporal Datasets using Deep Learning -- Learning Stochastic Dynamical Systems via Bridge Sampling -- Quantifying Quality of Actions Using Wearable Sensor -- An Initial Study on Adapting DTW at Individual Query for Electrocardiogram Analysis.
520 $a This book constitutes the refereed proceedings of the 4th ECML PKDD Workshop on Advanced Analytics and Learning on Temporal Data, AALTD 2019, held in Würzburg, Germany, in September 2019. The 7 full papers presented together with 9 poster papers were carefully reviewed and selected from 31 submissions. The papers cover topics such as temporal data clustering; classification of univariate and multivariate time series; early classification of temporal data; deep learning and learning representations for temporal data; modeling temporal dependencies; advanced forecasting and prediction models; space-temporal statistical analysis; functional data analysis methods; temporal data streams; interpretable time-series analysis methods; dimensionality reduction, sparsity, algorithmic complexity and big data challenge; and bio-informatics, medical, energy consumption, on temporal data. .
650 0 $a Artificial intelligence. $3 559380
650 0 $a Computers. $3 565115
650 0 $a Computer organization. $3 596298
650 0 $a Application software. $3 528147
650 0 $a Optical data processing. $3 639187
650 1 4 $a Artificial Intelligence. $3 646849
650 2 4 $a Information Systems and Communication Service. $3 669203
650 2 4 $a Computer Systems Organization and Communication Networks. $3 669309
650 2 4 $a Computer Applications. $3 669785
650 2 4 $a Computer Imaging, Vision, Pattern Recognition and Graphics. $3 671334
700 1 $a Lemaire, Vincent. $e editor. $1 https://orcid.org/0000-0002-6030-2356 $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1314574
700 1 $a Malinowski, Simon. $e editor. $1 https://orcid.org/0000-0002-9663-562X $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1314575
700 1 $a Bagnall, Anthony. $e editor. $1 https://orcid.org/0000-0003-2360-8994 $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1314576
700 1 $a Bondu, Alexis. $e editor. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1314577
700 1 $a Guyet, Thomas. $e editor. $1 https://orcid.org/0000-0002-4909-5843 $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1314578
700 1 $a Tavenard, Romain. $e editor. $1 https://orcid.org/0000-0002-1439-8465 $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1314579
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9783030390976
776 0 8 $i Printed edition: $z 9783030390990
830 0 $a Lecture Notes in Artificial Intelligence ; $v 9285 $3 1253845
856 4 0 $u https://doi.org/10.1007/978-3-030-39098-3
912 $a ZDB-2-SCS
912 $a ZDB-2-SXCS
912 $a ZDB-2-LNC
950 $a Computer Science (SpringerNature-11645)
950 $a Computer Science (R0) (SpringerNature-43710)