Name
Title | ||
|---|---|---|
A new feature selection method to improve the document clustering using particle swarm optimization algorithm. |
Abstract | ||
|---|---|---|
•Adapt PSO algorithm for the text feature selection problem.•A new feature selection method is established using the TF-IDF weight scheme.•K-mean text clustering is used based on the features obtained. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.jocs.2017.07.018 | Journal of Computational Science |
Keywords | Field | DocType |
00-01,99-00 | Data mining,Fuzzy clustering,CURE data clustering algorithm,Feature selection,Computer science,Artificial intelligence,Cluster analysis,Canopy clustering algorithm,Clustering high-dimensional data,Data stream clustering,Pattern recognition,Correlation clustering,Algorithm | Journal |
Volume | ISSN | Citations |
25 | 1877-7503 | 41 |
PageRank | References | Authors |
0.99 | 19 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Laith Mohammad Abualigah | 1 | 244 | 11.47 |
| Ahamad Tajudin Khader | 2 | 683 | 40.71 |
| Essam Said Hanandeh | 3 | 118 | 3.70 |