Identifying predictive multi-dimensional time series motifs: an application to severe weather prediction (original) (raw)

Mining Multidimensional Sequential Patterns over Data Streams

Il-Yeol Song

Lecture Notes in Computer Science, 2008

View PDFchevron_right

Mining sequential pattern of multi - dimensional wind profiles

Norhakim Yusof

2015

View PDFchevron_right

Mining causal relationships in multidimensional time series

Yasser F O Mohammad

2010

View PDFchevron_right

Mining Time-lagged Relationships in Spatio-Temporal Climate Data

Auroop Ganguly

View PDFchevron_right

Detecting Subdimensional Motifs: An Efficient Algorithm for Generalized Multivariate Pattern Discovery

Thad Starner

Seventh IEEE International Conference on Data Mining (ICDM 2007), 2007

View PDFchevron_right

Rare Time Series Motif Discovery from Unbounded Streams

Nurjahan Begum

2015

View PDFchevron_right

Mapping frequent spatio-temporal wind profile patterns using multi-dimensional sequential pattern mining

Norhakim Yusof

International Journal of Digital Earth, 2016

View PDFchevron_right

Analysis of Sequential pattern mining

Nikhil Gundawar

View PDFchevron_right

Classification of emerging extreme event tracks in multivariate spatio-temporal physical systems using dynamic network structures: application to hurricane track prediction

Zhengzhang (Zach) Chen, Fredrick Semazzi, Kumar Ramaiyer, Nagiza Samatova

2011

View PDFchevron_right

Spatial-time motifs discovery

Heraldo Borges

Intelligent Data Analysis, 2020

View PDFchevron_right

Time Series Data Mining: Identifying Temporal Patterns for Characterization and Prediction of Time Series Events

Richard Povinelli

View PDFchevron_right

Visual exploration of frequent patterns in multivariate time series

Ming Hao

Information Visualization, 2012

View PDFchevron_right

Forecast oriented classification of spatio-temporal extreme events

Zhengzhang (Zach) Chen

View PDFchevron_right

Pattern recognition in multivariate time series: dissertation proposal

Stephan Spiegel

2011

View PDFchevron_right

Enhancing understanding and improving prediction of severe weather through spatiotemporal relational learning

Jeffrey Basara

Machine Learning, 2014

View PDFchevron_right

Exploiting a novel algorithm and GPUs to break the ten quadrillion pairwise comparisons barrier for time series motifs and joins

Chin-Chia M. Yeh

Knowledge and Information Systems

View PDFchevron_right

New methods for mining sequential and time series data

Dr. Ghazi Al-Naymat

2009

View PDFchevron_right

Pattern recognition and classification for multivariate time series

Stephan Spiegel

2011

View PDFchevron_right

Severe Hail Prediction within a Spatiotemporal Relational Data Mining Framework

Amy McGovern

View PDFchevron_right

SPATIOTEMPORAL DATA MINING: ISSUES, TASKS AND APPLICATIONS

Agnes Rossi Trisna

View PDFchevron_right

Fingerprinting Significant Weather Events By

Jeremy Ross

2004

View PDFchevron_right

An enhanced representation of time series which allows fast and accurate classification, clustering and relevance feedback

Michael Pazzani

1998

View PDFchevron_right

Ranking and significance of variable-length similarity-based time series motifs

Alvaro Corral

View PDFchevron_right

Visualizing frequent patterns in large multivariate time series

Debprakash Patnaik

Visualization and Data Analysis 2011, 2011

View PDFchevron_right

Time Series Classification using Motifs and Characteristics Extraction: A Case Study on ECG Databases

Gustavo Batista

Procedings of the Fourth International Workshop on Knowledge Discovery, Knowledge Management and Decision Support, 2013

View PDFchevron_right

RPM: Representative Pattern Mining for Efficient Time Series Classification

Susan Frankenstein

2016

View PDFchevron_right

Experiencing SAX: a novel symbolic representation of time series

Li Wei

Data Mining and Knowledge Discovery, 2007

View PDFchevron_right

Motifs in time series for prediction - a naive approach compared to ARIMA

Nertila Ismailaja

View PDFchevron_right

Toward Understanding Tornado Formation Through Spatiotemporal Data Mining

Amy McGovern

Data Mining for Geoinformatics, 2013

View PDFchevron_right