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Pregled bibliografske jedinice broj: 364615

Časopis

Autori: Šilić, Artur; Moens, Marie-Francine; Žmak, Lovro; Dalbelo Bašić, Bojana
Naslov: Comparing Document Classification Schemes Using K-Means Clustering
Izvornik: Lecture Notes in Artificial Intelligence (0302-9743) 5177 (2008), 1; 615-624
Vrsta rada: članak
Ključne riječi: K-means; clustering; classification scheme; cluster visualization; PCA
Sažetak:
In this work, we jointly apply several text mining methods to a corpus of legal documents in order to compare the separation quality of two inherently different document classification schemes. The classification schemes are compared with the clusters produced by the K-means algorithm. In the future, we believe that our comparison method will be coupled with semi-supervised and active learning techniques. Also, this paper presents the idea of combining K-means and Principal Component Analysis for cluster visualization. The described idea allows calculations to be performed in reasonable amount of CPU time.
Projekt / tema: 036-1300646-1986
Izvorni jezik: ENG
Current Contents: NE
Citation Index: NE
Kategorija: Znanstveni
Znanstvena područja:
Računarstvo
Puni text rada: 364615.link.txt (tekst priložen 10. Vel. 2009. u 14:25 sati)
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OpenURL: http://www.springerlink.com/content/762g6125124t7362/
Google Scholar: Comparing Document Classification Schemes Using K-Means Clustering
Upisao u CROSBI: artur@fer.hr (artur@fer.hr), 8. Ruj. 2008. u 11:38 sati



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