Topic Clustering from Selected Area Papers

Park, Ho Hyun; Park, Jaehwa; Kwon, Young Bin

doi:10.17485/ijst/2015/v8i26/80470

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Birch Clustering Algorithm1

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Cited by 6 publications

(2 citation statements)

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“…Each node of this tree consists of various Clustering features. Three important parameters are required for the BIRCH algorithm: the threshold, the branching factor, and the number of clusters [7].…”

Section: Birch Clustering Algorithmmentioning

confidence: 99%

Subject Review: Text Clustering Algorithms

Ali

Kadhim

Abid

2020

IJERAT

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Clustering algorithms are taking attention in recent times, according to a huge amount of datasets and the growth of parallelized computing architectures. The goal of clustering algorithms is to divided the dataset into clusters, such that objects within the same cluster are similar to each other and differ from objects of other clusters. Clustering algorithms play an important role in information retrieval, indexing and text summarization. In this paper a brief overview of several clustering algorithms is discussed

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Section: Birch Clustering Algorithmmentioning

confidence: 99%

Subject Review: Text Clustering Algorithms

Ali

Kadhim

Abid

2020

IJERAT

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“…In [9], a statistical method called maximum entropy is used to classify Arabic news article. In [10], designed a multi-word term extraction method as a feature extraction of Arabic language. They used a hybrid method to extract multi-word terminology from Arabic corpus.…”

Section: Related Workmentioning

confidence: 99%