A review of clustering techniques and developments
This paper presents a comprehensive study on clustering: exiting methods and
developments made at various times. Clustering is defined as an unsupervised learning …
developments made at various times. Clustering is defined as an unsupervised learning …
A comprehensive survey of clustering algorithms: State-of-the-art machine learning applications, taxonomy, challenges, and future research prospects
AE Ezugwu, AM Ikotun, OO Oyelade… - … Applications of Artificial …, 2022 - Elsevier
Clustering is an essential tool in data mining research and applications. It is the subject of
active research in many fields of study, such as computer science, data science, statistics …
active research in many fields of study, such as computer science, data science, statistics …
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 …
A review on time series data mining
T Fu - Engineering Applications of Artificial Intelligence, 2011 - Elsevier
Time series is an important class of temporal data objects and it can be easily obtained from
scientific and financial applications. A time series is a collection of observations made …
scientific and financial applications. A time series is a collection of observations made …
A comparison study on similarity and dissimilarity measures in clustering continuous data
Similarity or distance measures are core components used by distance-based clustering
algorithms to cluster similar data points into the same clusters, while dissimilar or distant …
algorithms to cluster similar data points into the same clusters, while dissimilar or distant …
[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 …
[图书][B] Data mining: concepts and techniques
Data Mining: Concepts and Techniques, Fourth Edition introduces concepts, principles, and
methods for mining patterns, knowledge, and models from various kinds of data for diverse …
methods for mining patterns, knowledge, and models from various kinds of data for diverse …
Survey of clustering algorithms
Data analysis plays an indispensable role for understanding various phenomena. Cluster
analysis, primitive exploration with little or no prior knowledge, consists of research …
analysis, primitive exploration with little or no prior knowledge, consists of research …
BIRCH: an efficient data clustering method for very large databases
T Zhang, R Ramakrishnan, M Livny - ACM sigmod record, 1996 - dl.acm.org
Finding useful patterns in large datasets has attracted considerable interest recently, and
one of the most widely studied problems in this area is the identification of clusters, or …
one of the most widely studied problems in this area is the identification of clusters, or …
Clustering high-dimensional data: A survey on subspace clustering, pattern-based clustering, and correlation clustering
As a prolific research area in data mining, subspace clustering and related problems
induced a vast quantity of proposed solutions. However, many publications compare a new …
induced a vast quantity of proposed solutions. However, many publications compare a new …