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» Assessing the Significance of Sets of Words
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NIPS
2000
13 years 8 months ago
A Neural Probabilistic Language Model
A goal of statistical language modeling is to learn the joint probability function of sequences of words in a language. This is intrinsically difficult because of the curse of dim...
Yoshua Bengio, Réjean Ducharme, Pascal Vinc...
COLING
2008
13 years 9 months ago
Good Neighbors Make Good Senses: Exploiting Distributional Similarity for Unsupervised WSD
We present an automatic method for senselabeling of text in an unsupervised manner. The method makes use of distributionally similar words to derive an automatically labeled train...
Samuel Brody, Mirella Lapata
INFORMATICALT
1998
91views more  INFORMATICALT 1998»
13 years 7 months ago
Forecasting Automation: an Emerging Branch of Forecasting Engineering
Principles of the framework called time series forecasting automation are presented. It is required in processing massive temporal data sets and creating completely user-oriented f...
Andrey Kharchenko
GECCO
1999
Springer
145views Optimization» more  GECCO 1999»
13 years 11 months ago
Three Ways to Grow Designs: A Comparison of Embryogenies for an Evolutionary Design Problem
This paper explores the use of growth processes, or embryogenies, to map genotypes to phenotypes within evolutionary systems. Following a summary of the significant features of em...
Peter J. Bentley, Sanjeev Kumar
CICLING
2009
Springer
14 years 8 months ago
Improved Unsupervised Name Discrimination with Very Wide Bigrams and Automatic Cluster Stopping
We cast name discrimination as a problem in clustering short contexts. Each occurrence of an ambiguous name is treated independently, and represented using second?order context vec...
Ted Pedersen