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UM
2005
Springer
15 years 3 months ago
Data-Driven Refinement of a Probabilistic Model of User Affect
We present further developments in our work on using data from real users to build a probabilistic model of user affect based on Dynamic Bayesian Networks (DBNs) and designed to de...
Cristina Conati, Heather Maclaren
ICML
2005
IEEE
15 years 10 months ago
Exploiting syntactic, semantic and lexical regularities in language modeling via directed Markov random fields
We present a directed Markov random field (MRF) model that combines n-gram models, probabilistic context free grammars (PCFGs) and probabilistic latent semantic analysis (PLSA) fo...
Shaojun Wang, Shaomin Wang, Russell Greiner, Dale ...
DEXAW
2010
IEEE
202views Database» more  DEXAW 2010»
14 years 11 months ago
Identifying Sentence-Level Semantic Content Units with Topic Models
Abstract--Statistical approaches to document content modeling typically focus either on broad topics or on discourselevel subtopics of a text. We present an analysis of the perform...
Leonhard Hennig, Thomas Strecker, Sascha Narr, Ern...
ACL
2001
14 years 11 months ago
Parse Forest Computation of Expected Governors
In a headed tree, each terminal word can be uniquely labeled with a governing word and grammatical relation. This labeling is a summary of a syntactic analysis which eliminates de...
Helmut Schmid, Mats Rooth
MM
2009
ACM
269views Multimedia» more  MM 2009»
15 years 4 months ago
Semi-supervised topic modeling for image annotation
We propose a novel technique for semi-supervised image annotation which introduces a harmonic regularizer based on the graph Laplacian of the data into the probabilistic semantic ...
Yuanlong Shao, Yuan Zhou, Xiaofei He, Deng Cai, Hu...