- Autor
- Woźniak Rafał (Lodz University of Technology), Ożdżyński Piotr (Lodz University of Technology), Zakrzewska Danuata (Lodz University of Technology)
- Tytuł
- Cluster Analysis of Medical Text Documents by Using Semi-Clustering Approach Based on GRAPH Representation
- Źródło
- Information Systems in Management, 2018, vol. 7, nr 3, s. 213-224, rys., tab., bibliogr. 14 poz.
Systemy Informatyczne w Zarządzaniu - Słowa kluczowe
- Analiza skupień, Eksploracja tekstu
Cluster analysis, Text mining - Uwagi
- summ.
- Abstrakt
- The development of Internet resulted in an increasing number of online text repositories. In many cases, documents are assigned to more than one class and automatic multi-label classification needs to be used. When the number of labels exceeds the number of the documents, effective label space dimension reduction may significantly improve classification accuracy, what is a major priority in the medical field. In the paper, we propose document clustering for label selection. We use semi-clustering method, by considering graph representation, where documents are represented by vertices and edge weights are calculated according to their mutual similarity. Assigning documents to semi-clusters helps in reducing number of labels, further used in multi-label classification process. The performance of the method is examined by experiments conducted on real medical datasets. (original abstract)
- Pełny tekst
- Pokaż
- Bibliografia
-
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- Cytowane przez
- ISSN
- 2084-5537
- Język
- eng
- URI / DOI
- http://dx.doi.org/0.22630/ISIM.2018.7.3.19
