Title:	Easily labelling hierarchical document clusters.
Authors:	MOURA, M. F. MACACINI, R. M. REZENDE, S. O.
Affiliation:	MARIA FERNANDA MOURA, CNPTIA; RICARDO MARCONDES MARCACINI, USP; SOLANGE OLIVEIRA REZENDE, USP.
Date Issued:	2008
Citation:	In: SIMPÓSIO BRASILEIRO DE BANCO DE DADOS, 23.; SIMPÓSIO BRASILEIRO DE ENGENHARIA DE SOFTWARE, 22.; WORKSHOP EM ALGORITMOS E APLICAÇÕES DE MINERAÇÃO DE DADOS, 4., 2008, Campinas. Anais... Campinas: UNICAMP, Instituto de Computação, 2008.
Pages:	p. 37-45.
Description:	One of the problems of automatic models that generate topic taxonomies is the process of creating the most significant term list that discriminates each document group. In this paper, a new method to label document hierarchical clusters is proposed, which is completely independent from the clustering method. This method automatically decides the number of the words in each label list, avoids word repetitions in a tree branch and provides a kind of cutting for the cluster tree. The obtained results were tested as search queries in a retrieval process and showed a very good performance. Additionally, the use of the method was experimented by some specialists in the text collection domain, trying to evaluate their understanding and expectations over the results.
Thesagro:	Taxonomia
NAL Thesaurus:	Cluster analysis Taxonomy
Keywords:	Dados semânticos
Type of Material:	Artigo em anais e proceedings
Access:	openAccess
Appears in Collections:	Artigo em anais de congresso (CNPTIA)