An Improved Clustering Algorithm for Text Mining: Multi-Cluster Spherical K-Means
Küçük Resim Yok
Tarih
2016
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
ZARKA PRIVATE UNIV
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Thanks to advances in information and communication technologies, there is a prominent increase in the amount of information produced specifically in the form of text documents. In order to, effectively deal with this "information explosion" problem and utilize the huge amount of text databases, efficient and scalable tools and techniques are indispensable. In this study, text clustering which is one of the most important techniques of text mining that aims at extracting useful information by processing data in textual form is addressed. An improved variant of spherical K-Means (SKM) algorithm named multi-cluster SKM is developed for clustering high dimensional document collections with high performance and efficiency. Experiments were performed on several document data sets and it is shown that the new algorithm provides significant increase in clustering quality without causing considerable difference in CPU time usage when compared to SKM algorithm.
Açıklama
Anahtar Kelimeler
Data mining, text mining, document clustering, SKM
Kaynak
INTERNATIONAL ARAB JOURNAL OF INFORMATION TECHNOLOGY
WoS Q Değeri
Q4
Scopus Q Değeri
Q3
Cilt
13
Sayı
1
