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» Learning probabilistic models of the Web
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ITCC
2005
IEEE
15 years 11 months ago
A Scalable Generative Topographic Mapping for Sparse Data Sequences
We propose a novel, computationally efficient generative topographic model for inferring low dimensional representations of high dimensional data sets, designed to exploit data s...
Ata Kabán
LREC
2008
145views Education» more  LREC 2008»
15 years 6 months ago
BOEMIE Ontology-Based Text Annotation Tool
The huge amount of the available information in the Web creates the need of effective information extraction systems that are able to produce metadata that satisfy user's inf...
Pavlina Fragkou, Georgios Petasis, Aris Theodorako...
NN
1998
Springer
177views Neural Networks» more  NN 1998»
15 years 5 months ago
Soft vector quantization and the EM algorithm
The relation between hard c-means (HCM), fuzzy c-means (FCM), fuzzy learning vector quantization (FLVQ), soft competition scheme (SCS) of Yair et al. (1992) and probabilistic Gaus...
Ethem Alpaydin
SIGIR
2011
ACM
14 years 8 months ago
Parameterized concept weighting in verbose queries
The majority of the current information retrieval models weight the query concepts (e.g., terms or phrases) in an unsupervised manner, based solely on the collection statistics. I...
Michael Bendersky, Donald Metzler, W. Bruce Croft
139
Voted
TNN
1998
123views more  TNN 1998»
15 years 5 months ago
A general framework for adaptive processing of data structures
—A structured organization of information is typically required by symbolic processing. On the other hand, most connectionist models assume that data are organized according to r...
Paolo Frasconi, Marco Gori, Alessandro Sperduti