Bioinformatics—an introduction for computer scientists
J Cohen - ACM Computing Surveys (CSUR), 2004 - dl.acm.org
The article aims to introduce computer scientists to the new field of bioinformatics. This area
has arisen from the needs of biologists to utilize and help interpret the vast amounts of data …
has arisen from the needs of biologists to utilize and help interpret the vast amounts of data …
k-shape: Efficient and accurate clustering of time series
J Paparrizos, L Gravano - Proceedings of the 2015 ACM SIGMOD …, 2015 - dl.acm.org
The proliferation and ubiquity of temporal data across many disciplines has generated
substantial interest in the analysis and mining of time series. Clustering is one of the most …
substantial interest in the analysis and mining of time series. Clustering is one of the most …
Toward non-intrusive load monitoring via multi-label classification
Demand-side management technology is a key element of the proposed smart grid, which
will help utilities make more efficient use of their generation assets by reducing consumers' …
will help utilities make more efficient use of their generation assets by reducing consumers' …
A global averaging method for dynamic time warping, with applications to clustering
F Petitjean, A Ketterlin, P Gançarski - Pattern recognition, 2011 - Elsevier
Mining sequential data is an old topic that has been revived in the last decade, due to the
increasing availability of sequential datasets. Most works in this field are centred on the …
increasing availability of sequential datasets. Most works in this field are centred on the …
[图书][B] Data clustering: theory, algorithms, and applications
The monograph Data Clustering: Theory, Algorithms, and Applications was published in
2007. Starting with the common ground and knowledge for data clustering, the monograph …
2007. Starting with the common ground and knowledge for data clustering, the monograph …
Exact indexing of dynamic time warping
E Keogh, CA Ratanamahatana - Knowledge and information systems, 2005 - Springer
The problem of indexing time series has attracted much interest. Most algorithms used to
index time series utilize the Euclidean distance or some variation thereof. However, it has …
index time series utilize the Euclidean distance or some variation thereof. However, it has …
[图书][B] Dynamic bayesian networks: representation, inference and learning
KP Murphy - 2002 - search.proquest.com
Modelling sequential data is important in many areas of science and engineering. Hidden
Markov models (HMMs) and Kalman filter models (KFMs) are popular for this because they …
Markov models (HMMs) and Kalman filter models (KFMs) are popular for this because they …
[图书][B] Clustering
R Xu, D Wunsch - 2008 - books.google.com
This is the first book to take a truly comprehensive look at clustering. It begins with an
introduction to cluster analysis and goes on to explore: proximity measures; hierarchical …
introduction to cluster analysis and goes on to explore: proximity measures; hierarchical …
Fast and accurate time-series clustering
J Paparrizos, L Gravano - ACM Transactions on Database Systems …, 2017 - dl.acm.org
The proliferation and ubiquity of temporal data across many disciplines has generated
substantial interest in the analysis and mining of time series. Clustering is one of the most …
substantial interest in the analysis and mining of time series. Clustering is one of the most …
Clustering of time-series subsequences is meaningless: implications for previous and future research
Given the recent explosion of interest in streaming data and online algorithms, clustering of
time-series subsequences, extracted via a sliding window, has received much attention. In …
time-series subsequences, extracted via a sliding window, has received much attention. In …