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» Modeling word burstiness using the Dirichlet distribution
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PKDD
2009
Springer
175views Data Mining» more  PKDD 2009»
15 years 6 months ago
Latent Dirichlet Bayesian Co-Clustering
Co-clustering has emerged as an important technique for mining contingency data matrices. However, almost all existing coclustering algorithms are hard partitioning, assigning each...
Pu Wang, Carlotta Domeniconi, Kathryn B. Laskey
EDM
2010
113views Data Mining» more  EDM 2010»
15 years 1 months ago
Using multiple Dirichlet distributions to improve parameter plausibility
Predictive accuracy and parameter plausibility are two major desired aspects for a student modeling approach. Knowledge tracing, the most commonly used approach, suffers from local...
Yue Gong, Joseph E. Beck, Neil T. Heffernan
AAAI
2010
14 years 9 months ago
Latent Class Models for Algorithm Portfolio Methods
Different solvers for computationally difficult problems such as satisfiability (SAT) perform best on different instances. Algorithm portfolios exploit this phenomenon by predicti...
Bryan Silverthorn, Risto Miikkulainen
EMNLP
2011
13 years 11 months ago
Cross-Cutting Models of Lexical Semantics
Context-dependent word similarity can be measured over multiple cross-cutting dimensions. For example, lung and breath are similar thematically, while authoritative and superfici...
Joseph Reisinger, Raymond J. Mooney
SIGIR
2008
ACM
14 years 11 months ago
A new probabilistic retrieval model based on the dirichlet compound multinomial distribution
The classical probabilistic models attempt to capture the Ad hoc information retrieval problem within a rigorous probabilistic framework. It has long been recognized that the prim...
Zuobing Xu, Ram Akella