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» Probabilistic topic modeling for genomic data interpretation
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ML
2008
ACM
150views Machine Learning» more  ML 2008»
14 years 9 months ago
Learning probabilistic logic models from probabilistic examples
Abstract. We revisit an application developed originally using Inductive Logic Programming (ILP) by replacing the underlying Logic Program (LP) description with Stochastic Logic Pr...
Jianzhong Chen, Stephen Muggleton, José Car...
ESANN
2007
14 years 11 months ago
Visualisation of tree-structured data through generative probabilistic modelling
We present a generative probabilistic model for the topographic mapping of tree structured data. The model is formulated as constrained mixture of hidden Markov tree models. A nat...
Nikolaos Gianniotis, Peter Tino
PKDD
2010
Springer
313views Data Mining» more  PKDD 2010»
14 years 7 months ago
Topic Modeling for Personalized Recommendation of Volatile Items
One of the major strengths of probabilistic topic modeling is the ability to reveal hidden relations via the analysis of co-occurrence patterns on dyadic observations, such as docu...
Maks Ovsjanikov, Ye Chen
ICDM
2007
IEEE
184views Data Mining» more  ICDM 2007»
15 years 3 months ago
Bayesian Folding-In with Dirichlet Kernels for PLSI
Probabilistic latent semantic indexing (PLSI) represents documents of a collection as mixture proportions of latent topics, which are learned from the collection by an expectation...
Alexander Hinneburg, Hans-Henning Gabriel, Andr&eg...
CORR
2012
Springer
220views Education» more  CORR 2012»
13 years 5 months ago
Sparse Topical Coding
We present sparse topical coding (STC), a non-probabilistic formulation of topic models for discovering latent representations of large collections of data. Unlike probabilistic t...
Jun Zhu, Eric P. Xing