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020			_a9783031498961 _9978-3-031-49896-1
024	7		_a10.1007/978-3-031-49896-1 _2doi
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245	1	0	_aAdvanced Analytics and Learning on Temporal Data _h[electronic resource] : _b8th ECML PKDD Workshop, AALTD 2023, Turin, Italy, September 18-22, 2023, Revised Selected Papers / _cedited by Georgiana Ifrim, Romain Tavenard, Anthony Bagnall, Patrick Schaefer, Simon Malinowski, Thomas Guyet, Vincent Lemaire.
250			_a1st ed. 2023.
264		1	_aCham : _bSpringer Nature Switzerland : _bImprint: Springer, _c2023.
300			_aXIII, 308 p. 113 illus., 90 illus. in color. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	1		_aLecture Notes in Artificial Intelligence, _x2945-9141 ; _v14343
505	0		_aHuman Activity Segmentation Challenge -- Human Activity Segmentation Challenge@ECML/PKDD'23 -- Change points detection in multivariate signal applied to human activity segmentation -- Change Point Detection via Synthetic Signals -- Oral Presentation -- Clustering time series with k-medoids based algorithms -- Explainable Parallel RCNN with Novel Feature Representation for Time Series Forecasting -- RED CoMETS: an ensemble classifier for symbolically represented multivariate time series -- Deep Long Term Prediction for Semantic Segmentation in Autonomous Driving -- Extracting Features from Random Subseries: A Hybrid Pipeline for Time Series Classification and Extrinsic Regression -- ShapeDBA: Generating Effective Time Series Prototypes using ShapeDTW Barycenter Averaging -- Poster Presentation -- Temporal Performance Prediction for Deep Convolutional Long Short-Term Memory Networks -- Evaluating Explanation Methods for Multivariate Time Series Classification -- tGLAD: A sparse graph recovery based approach for multivariate time series segmentation -- Designing a New Search Space for Multivariate Time-Series Neural Architecture Search -- Back to Basics: A Sanity Check on Modern Time Series Classification Algorithms -- Do Cows Have Fingerprints? Using Time Series Techniques and Milk Flow Profiles to Characterise Cow Behaviours and Detect Health Issues -- Exploiting Context and Attention with Recurrent Neural Network for Sensor Time Series Prediction -- Rail Crack Propagation Forecasting Using Multi-horizons RNNs -- Electricity Load and Peak Forecasting: Feature Engineering, Probabilistic LightGBM and Temporal Hierarchies -- Time-aware Predictions of Moments of Change in Longitudinal User Posts on Social Media.
520			_aThis volume LNCS 14343 constitutes the refereed proceedings of the 8th ECML PKDD Workshop, AALTD 2023, in Turin, Italy, in September 2023. The 20 full papers were carefully reviewed and selected from 28 submissions. They are organized in the following topical section as follows: Machine Learning; Data Mining; Pattern Analysis; Statistics to Share their Challenges and Advances in Temporal Data Analysis. .
650		0	_aArtificial intelligence. _93407
650	1	4	_aArtificial Intelligence. _93407
700	1		_aIfrim, Georgiana. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt _9174706
700	1		_aTavenard, Romain. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt _9174707
700	1		_aBagnall, Anthony. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt _9174708
700	1		_aSchaefer, Patrick. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt _9174709
700	1		_aMalinowski, Simon. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt _9174710
700	1		_aGuyet, Thomas. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt _9174711
700	1		_aLemaire, Vincent. _eeditor. _0(orcid) _10000-0002-6030-2356 _4edt _4http://id.loc.gov/vocabulary/relators/edt _9174712
710	2		_aSpringerLink (Online service) _9174713
773	0		_tSpringer Nature eBook
776	0	8	_iPrinted edition: _z9783031498954
776	0	8	_iPrinted edition: _z9783031498978
830		0	_aLecture Notes in Artificial Intelligence, _x2945-9141 ; _v14343 _9174714
856	4	0	_uhttps://doi.org/10.1007/978-3-031-49896-1
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