A sparse version of the ridge logistic regression for large-scale text categorization

Autor: Eric Gaussier, Yves Denneulin, Sujeevan Aseervatham, Anestis Antoniadis, Michel Burlet

Publikováno v: Pattern Recognition Letters
Pattern Recognition Letters, Elsevier, 2011, 32 (2), pp.101-106. ⟨10.1016/j.patrec.2010.09.023⟩
Pattern Recognition Letters, 2011, 32 (2), pp.101-106. ⟨10.1016/j.patrec.2010.09.023⟩

International audience; The ridge logistic regression has successfully been used in text categorization problems and it has been shown to reach the same performance as the Support Vector Machine but with the main advantage of computing a probability

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f2d37c7343bd8da7454cd5df762ea2ee
https://hal.archives-ouvertes.fr/hal-00633629/file/Aseervatham-PatternRecognitionLetter2011.pdf

A Local Latent Semantic Analysis-based Kernel for Document Similarities

Autor: Sujeevan Aseervatham

Publikováno v: Neural Networks, 2008. IJCNN 2008. (IEEE World Congress on Computational Intelligence). IEEE International Joint Conference on Neural Networks
IEEE International Joint Conference on Neural Networks
IEEE International Joint Conference on Neural Networks, Jun 2008, Hong-Kong, China. pp.214-219, ⟨10.1109/IJCNN.2008.4633792⟩
IJCNN

International audience; The document similarity measure is a key point in textual data processing. It is the main responsible of the performance of a processing system. Since a decade, kernels are used as similarity functions within inner-product bas

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a4c393c68bf89d241186fd79b171728d
https://hal.archives-ouvertes.fr/hal-00339857

A Concept Vector Space Model for Semantic Kernels

Autor: Sujeevan Aseervatham

Publikováno v: International Journal on Artificial Intelligence Tools
International Journal on Artificial Intelligence Tools, World Scientific Publishing, 2008, 18 (2), To appear
HAL

International audience; Kernels are widely used in Natural Language Processing as similarity measures within inner-product based learning methods like the Support Vector Machine. The Vector Space Model (VSM) is extensively used for the spatial repres

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f9c0721ef9a0b73180938bf19faaaad7
https://hal.archives-ouvertes.fr/hal-00339916

bitSPADE: A Lattice-Based Sequential Pattern Mining Algorithm Using Bitmap Representation

Autor: Aomar Osmani, Emmanuel Viennet, Sujeevan Aseervatham

Publikováno v: ICDM
Proceedings of the Sixth International Conference on Data Mining (ICDM'06)
International Conference on Data Mining (ICDM'06)
International Conference on Data Mining (ICDM'06), 2006, Hong Kong SAR China. pp.6
HAL

Sequential pattern mining allows to discover temporal relationship between items within a database. The patterns can then be used to generate association rules. When the databases are very large, the execution speed and the memory usage of the mining

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b4dfc9a054bfc305e48caf85c83b8907
https://hal.archives-ouvertes.fr/hal-00153979

Mining short sequential patterns for hepatitis type detection

Autor: Sujeevan Aseervatham, Aomar OSMANI

Publikováno v: HAL
Proceedings of the ECML/PKDD 2005 Discovery Challenge
ECML/PKDD 2005-Discovery Challenge Workshop
ECML/PKDD 2005-Discovery Challenge Workshop, 2005, Portugal. pp.6

International audience; This paper presents the framework we have developed to classify patients according to the type of hepatitis. To detect the type of virus, once the data have been prepared and encoded in a suitable way, we have extracted the se

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::8c6fea9bf8f7d2625dd85273bd88f8fc
https://hal.archives-ouvertes.fr/hal-00153970