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What is Partitioning Clustering

Handbook of Research on Innovations in Database Technologies and Applications: Current and Future Trends
It is a clustering approach which uses centers to represent clusters and then improves the partitioning by moving objects from group to group.
Published in Chapter:
Data Clustering
Yanchang Zhao (University of Technology - Sydney, Australia), Longbing Cao (University of Technology - Sydney, Australia), Huaifeng Zhang (University of Technology - Sydney, Australia), and Chengqi Zhang (University of Technology - Sydney, Australia)
DOI: 10.4018/978-1-60566-242-8.ch060
Clustering is one of the most important techniques in data mining. This chapter presents a survey of popular approaches for data clustering, including well-known clustering techniques, such as partitioning clustering, hierarchical clustering, density-based clustering and grid-based clustering, and recent advances in clustering, such as subspace clustering, text clustering and data stream clustering. The major challenges and future trends of data clustering will also be introduced in this chapter. The remainder of this chapter is organized as follows. The background of data clustering will be introduced in Section 2, including the definition of clustering, categories of clustering techniques, features of good clustering algorithms, and the validation of clustering. Section 3 will present main approaches for clustering, which range from the classic partitioning and hierarchical clustering to recent approaches of bi-clustering and semisupervised clustering. Challenges and future trends will be discussed in Section 4, followed by the conclusions in the last section.
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More Results
Swarm Intelligence in Text Document Clustering
The partitioning clustering method seeks to partition a collection of documents into a set of non-overlapping groups, so as to maximize the evaluation value of clustering.
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Categorization of Data Clustering Techniques
Partitioning clustering is the process of generating a single partition of the data in an attempt to recover any natural groupings hidden in the data.
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