Journal
SOFT COMPUTING
Volume 20, Issue 6, Pages 2329-2339Publisher
SPRINGER
DOI: 10.1007/s00500-015-1643-3
Keywords
-
Categories
Funding
- Spanish Ministry of Education under the Programa de Formacion del Profesorado Universitario (FPU)
- Short Stays Program from CEI-Biotic (University of Granada)
Ask authors/readers for more resources
In the last times, semi-supervised clustering has been an area that has received a lot of attention. It is distinguished from more traditional unsupervised approaches on the use of a small amount of supervision to steer clustering. Unfortunately in the real world, the supervision is not always available: data to process are often too large and so the cost (in terms of time and human resources) for user-provided information is not conceivable. To address this issue, this work presents an automatic generation of the supervision, by the analysis of the data structure itself. This analysis is performed using a partitional clustering algorithm that discovers relationships between pairs of instances that may be used as a semi-supervision in the clustering process. The methodology has been studied in the document clustering domain, an area where novel approaches for accurate documents classifications are strongly required. Experimental result shows the validity of this approach.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available