PLSI: The True Fisher Kernel and beyond IID Processes, Information Matrix and Model Identification in PLSI

The Probabilistic Latent Semantic indexing model, introduced by T. Hofmann (1999), has engendered applications ill numerous fields, notably document classification and information retrieval. In this context, the Fisher kernel was found to be an appropriate document similarity measure. However, the kernels published so far contain unjustified features, some of which hinder their performances. Furthermore, PLSI is not generative for unknown documents, a shortcoming usually remedied by "folding them in" the PLSI parameter space.


Published in:
Machine Learning And Knowledge Discovery In Databases, Pt I, 5781, 195-210
Presented at:
Joint European Conference on Machine Learning (ECML)/European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD), Bled, SLOVENIA, Sep 07-11, 2009
Year:
2009
Publisher:
Springer-Verlag New York, Ms Ingrid Cunningham, 175 Fifth Ave, New York, Ny 10010 Usa
Keywords:
Laboratories:




 Record created 2010-11-30, last modified 2018-03-17


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