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IRCDL
2007
13 years 9 months ago
An Hybrid Approach for Improving Word Sense Disambiguation and Text Clustering
Abstract— In this paper we suggest a new approach to represent text document collections, integrating background knowledge to improve clustering effectiveness. Background knowled...
Paolo Casoto, Carlo Tasso
ICDM
2003
IEEE
119views Data Mining» more  ICDM 2003»
14 years 29 days ago
A Dynamic Adaptive Self-Organising Hybrid Model for Text Clustering
Clustering by document concepts is a powerful way of retrieving information from a large number of documents. This task in general does not make any assumption on the data distrib...
Chihli Hung, Stefan Wermter
22
Voted
KDD
2002
ACM
179views Data Mining» more  KDD 2002»
14 years 8 months ago
Combining clustering and co-training to enhance text classification using unlabelled data
In this paper, we present a new co-training strategy that makes use of unlabelled data. It trains two predictors in parallel, with each predictor labelling the unlabelled data for...
Bhavani Raskutti, Herman L. Ferrá, Adam Kow...
CIKM
2004
Springer
14 years 1 months ago
Stemming and lemmatization in the clustering of finnish text documents
Under construction… Categories and Subject Descriptors H.3.3 [Information Storage and Retrieval]: Information Search and Retrieval – clustering. General Terms Algorithms, Expe...
Tuomo Korenius, Jorma Laurikkala, Kalervo Jär...
ICDM
2003
IEEE
210views Data Mining» more  ICDM 2003»
14 years 29 days ago
CBC: Clustering Based Text Classification Requiring Minimal Labeled Data
Semi-supervised learning methods construct classifiers using both labeled and unlabeled training data samples. While unlabeled data samples can help to improve the accuracy of trai...
Hua-Jun Zeng, Xuanhui Wang, Zheng Chen, Hongjun Lu...