Name
Abstract | ||
|---|---|---|
•We propose an efficient KL-based word clustering algorithm for large-scale text collection.•The word clusters were adopted as features to enhance the sequential taggers.•The use of word clusters improves the prediction power (using statistical significant tests). |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1016/j.ins.2014.02.033 | Information Sciences |
Keywords | Field | DocType |
Large-scale word clustering,Phrase chunking,Support vector machine | Fuzzy clustering,CURE data clustering algorithm,Semi-supervised learning,Computer science,Natural language processing,Artificial intelligence,Cluster analysis,Canopy clustering algorithm,Data stream clustering,Correlation clustering,Pattern recognition,Determining the number of clusters in a data set,Machine learning | Journal |
Volume | ISSN | Citations |
275 | 0020-0255 | 4 |
PageRank | References | Authors |
0.38 | 37 | 1 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yu-Chieh Wu | 1 | 247 | 23.16 |