Spatio-temporal data mining: A survey of problems and methods
Large volumes of spatio-temporal data are increasingly collected and studied in diverse
domains, including climate science, social sciences, neuroscience, epidemiology …
domains, including climate science, social sciences, neuroscience, epidemiology …
The great time series classification bake off: a review and experimental evaluation of recent algorithmic advances
In the last 5 years there have been a large number of new time series classification
algorithms proposed in the literature. These algorithms have been evaluated on subsets of …
algorithms proposed in the literature. These algorithms have been evaluated on subsets of …
An empirical survey of data augmentation for time series classification with neural networks
In recent times, deep artificial neural networks have achieved many successes in pattern
recognition. Part of this success can be attributed to the reliance on big data to increase …
recognition. Part of this success can be attributed to the reliance on big data to increase …
Data validation for machine learning
Abstract Machine learning is a powerful tool for gleaning knowledge from massive amounts
of data. While a great deal of machine learning research has focused on improving the …
of data. While a great deal of machine learning research has focused on improving the …
Matrix profile I: all pairs similarity joins for time series: a unifying view that includes motifs, discords and shapelets
The all-pairs-similarity-search (or similarity join) problem has been extensively studied for
text and a handful of other datatypes. However, surprisingly little progress has been made …
text and a handful of other datatypes. However, surprisingly little progress has been made …
[كتاب][B] Data cleaning
This is an overview of the end-to-end data cleaning process. Data quality is one of the most
important problems in data management, since dirty data often leads to inaccurate data …
important problems in data management, since dirty data often leads to inaccurate data …
Time-series clustering–a decade review
Clustering is a solution for classifying enormous data when there is not any early knowledge
about classes. With emerging new concepts like cloud computing and big data and their vast …
about classes. With emerging new concepts like cloud computing and big data and their vast …
k-shape: Efficient and accurate clustering of time series
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 …
A review on distance based time series classification
Time series classification is an increasing research topic due to the vast amount of time
series data that is being created over a wide variety of fields. The particularity of the data …
series data that is being created over a wide variety of fields. The particularity of the data …
[كتاب][B] An introduction to outlier analysis
CC Aggarwal, CC Aggarwal - 2017 - Springer
Outliers are also referred to as abnormalities, discordants, deviants, or anomalies in the data
mining and statistics literature. In most applications, the data is created by one or more …
mining and statistics literature. In most applications, the data is created by one or more …