- Tytuł:
- Cluster analysis of medical text documents by using semi-clustering approach based on graph representation
- Autorzy:
-
Woźniak, R.
Ożdżyński, P.
Zakrzewska, D. - Powiązania:
- https://bibliotekanauki.pl/articles/94773.pdf
- Data publikacji:
- 2018
- Wydawca:
- Szkoła Główna Gospodarstwa Wiejskiego w Warszawie. Wydawnictwo Szkoły Głównej Gospodarstwa Wiejskiego w Warszawie
- Tematy:
-
cluster analysis
semi-clustering
text mining - Opis:
- 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 semiclustering 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.
- Źródło:
-
Information Systems in Management; 2018, 7, 3; 213-224
2084-5537
2544-1728 - Pojawia się w:
- Information Systems in Management
- Dostawca treści:
- Biblioteka Nauki
Artykuł