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» Hierarchical Document Clustering using Frequent Itemsets
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IMCSIT
2010
13 years 5 months ago
Learning taxonomic relations from a set of text documents
This paper presents a methodology for learning taxonomic relations from a set of documents that each explain one of the concepts. Three different feature extraction approaches with...
Mari-Sanna Paukkeri, Alberto Pérez Garc&iac...
LAWEB
2006
IEEE
14 years 1 months ago
Where and How Duplicates Occur in the Web
In this paper we study duplicates on the Web, using collections containing documents of all sites under the .cl domain that represent accurate and representative subsets of the We...
Álvaro R. Pereira Jr., Ricardo A. Baeza-Yat...
EMNLP
2009
13 years 5 months ago
Hypernym Discovery Based on Distributional Similarity and Hierarchical Structures
This paper presents a new method of developing a large-scale hyponymy relation database by combining Wikipedia and other Web documents. We attach new words to the hyponymy databas...
Ichiro Yamada, Kentaro Torisawa, Jun'ichi Kazama, ...
DAS
2008
Springer
13 years 9 months ago
A Comparison of Clustering Methods for Word Image Indexing
In this paper we explore the effectiveness of three clustering methods used to perform word image indexing. The three methods are: the Self-Organazing Map (SOM), the Growing Hiera...
Simone Marinai, Emanuele Marino, Giovanni Soda
SAC
2005
ACM
14 years 1 months ago
A hierarchical naive Bayes mixture model for name disambiguation in author citations
Because of name variations, an author may have multiple names and multiple authors may share the same name. Such name ambiguity affects the performance of document retrieval, web ...
Hui Han, Wei Xu, Hongyuan Zha, C. Lee Giles