Foundations of statistical natural language processing
Foundations of statistical natural language processing
A Comparative Study on Feature Selection in Text Categorization
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
Recognizing text genres with simple metrics using discriminant analysis
COLING '94 Proceedings of the 15th conference on Computational linguistics - Volume 2
Briefly noted: modes of discourse: The local structure of texts
Computational Linguistics
Can shared-neighbor distances defeat the curse of dimensionality?
SSDBM'10 Proceedings of the 22nd international conference on Scientific and statistical database management
Euclidean distances, soft and spectral clustering on weighted graphs
ECML PKDD'10 Proceedings of the 2010 European conference on Machine learning and knowledge discovery in databases: Part I
On the Schoenberg Transformations in Data Analysis: Theory and Illustrations
Journal of Classification
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To cluster textual sequence types (discourse types/modes) in French texts, K-means algorithm with high-dimensional embeddings and fuzzy clustering algorithm were applied on clauses whose POS (part-of speech) n-gram profiles were previously extracted. Uni-, bi- and trigrams were used on four 19th century French short stories by Maupassant. For high-dimensional embeddings, power transformations on the chisquared distances between clauses were explored. Preliminary results show that highdimensional embeddings improve the quality of clustering, contrasting the use of bi- and trigrams whose performance is disappointing, possibly because of feature space sparsity.