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This paper presents a new metric to compute similarities between textual documents, based on the Fisher information kernel as proposed by T. Hofmann.
This paper presents a new metric to compute similarities between textual documents, based on the Fisher information kernel as proposed by T. Hofmann.
This paper presents a new metric to compute similarities between textual documents, based on the Fisher information kernel as proposed by T. Hofmann.
Abstract. This paper presents a new metric to compute similarities between textual documents, based on the Fisher information kernel as.
Type. conference paper ; Publication date. 2006 ; Published in. Machine Learning: ECML 2006 ; Start page. 727 ; End page. 734.
This paper presents a new metric to compute similarities between textual documents, based on the Fisher information kernel as proposed by T. Hofmann.
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Revisiting Fisher Kernels for Document Similarities. Author. Chappelier Jean-Cédric · Gaussier Eric · Nyffenegger Martin. Publication venue: 'Springer Science ...
Martin Nyffenegger, Jean-Cédric Chappelier, Éric Gaussier: Revisiting Fisher Kernels for Document Similarities. ECML 2006: 727-734.
Revisiting Fisher Kernels for Document Similarities. 727-734. view. electronic edition via DOI (open access) · references & citations. authority control ...