A Clustering Algorithm Based on Generalized Stars

Suárez, Airel Pérez; Pagola, José E. Medina

doi:10.1007/978-3-540-73499-4_19

Cited by 9 publications

(1 citation statement)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Some examples of this kind of applications are information retrieval [1], social network analysis [2], text segmentation [3], among others. In the literature, several algorithms have been proposed for overlapping clustering [4,5,6,7,8,9,10,11], which are different according to their mathematical basis and clustering strategies, as well as the type of datasets they can process. Due to their simplicity, the Kmeans algorithm [12] together with its variants are clustering algorithms that have been widely used in several applications.…”

Section: Introductionmentioning

confidence: 99%

Study of Overlapping Clustering Algorithms Based on Kmeans through FBcubed Metric

Aroche-Villarruel

Carrasco-Ochoa

Martínez-Trinidad

et al. 2014

Lecture Notes in Computer Science

View full text Add to dashboard Cite

In this paper we present a study of the overlapping clustering algorithms OKM, WOKM and OKMED, which are extensions to the overlapping case of the well known Kmeans algorithm proposed for building partitions. Different to other previously reported comparisons, in our study we compare these algorithms using the external evaluation metric FBcubed which takes into account the overlapping among clusters and we contrast our results against those obtained by F-measure, a metric that does not take into account the overlapping among clusters and that has been previously used in another reported comparison.

show abstract

Section: Introductionmentioning

confidence: 99%

Study of Overlapping Clustering Algorithms Based on Kmeans through FBcubed Metric

Aroche-Villarruel

Carrasco-Ochoa

Martínez-Trinidad

et al. 2014

Lecture Notes in Computer Science

View full text Add to dashboard Cite

show abstract

Hierarchical Star Clustering Algorithm for Dynamic Document Collections

Gil-García

Pons-Porrata

2008

Lecture Notes in Computer Science

View full text Add to dashboard Cite

Abstract. In this paper, a new clustering algorithm called Dynamic Hierarchical Star is introduced. Our approach aims to construct a hierarchy of overlapped clusters, dealing with dynamic data sets. The experimental results on several benchmark text collections show that this method obtains smaller hierarchies than traditional algorithms while achieving a similar clustering quality. Therefore, we advocate its use for tasks that require dynamic overlapped clustering, such as information organization, creation of document taxonomies and hierarchical topic detection.

show abstract

A New Incremental Algorithm for Overlapped Clustering

Suárez

Martínez-Trinidad

Carrasco-Ochoa

et al. 2009

Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications

Self Cite

View full text Add to dashboard Cite

In this paper, a new algorithm for incremental overlapped clustering, called Incremental Clustering by Strength Decision (ICSD), is introduced. ICSD obtains a set of dense and overlapped clusters using a new graph cover heuristic while reduces the amount of computation by maintaining incrementally the cluster structure. The experimental results show that our proposal outperforms other graph-based clustering algorithms considering quality measures and also show that ICSD achieves a better time performance than other incremental graph-based algorithms.

show abstract

A Clustering Algorithm Based on Generalized Stars

Cited by 9 publications

References 9 publications

Study of Overlapping Clustering Algorithms Based on Kmeans through FBcubed Metric

Study of Overlapping Clustering Algorithms Based on Kmeans through FBcubed Metric

Hierarchical Star Clustering Algorithm for Dynamic Document Collections

A New Incremental Algorithm for Overlapped Clustering

Contact Info

Product

Resources

About