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» Learning Rational Stochastic Languages
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KI
2007
Springer
14 years 1 months ago
Extending Markov Logic to Model Probability Distributions in Relational Domains
Abstract. Markov logic, as a highly expressive representation formalism that essentially combines the semantics of probabilistic graphical models with the full power of first-orde...
Dominik Jain, Bernhard Kirchlechner, Michael Beetz
SIGITE
2004
ACM
14 years 1 months ago
Implementation of object-orientation using UML in entry level software development courses
In this paper, we establish the need (based on literature and anecdotal evidence) for an infrastructure for CS1 courses to visually support problem solving from the initial proble...
Mohammad H. N. Tabrizi, Carol B. Collins, E. Ozan,...
ANLP
1992
86views more  ANLP 1992»
13 years 8 months ago
A Simple Rule-Based Part of Speech Tagger
Automatic part of speech tagging is an area of natural language processing where statistical techniques have been more successful than rule-based methods. In this paper, we presen...
Eric Brill
SIGMOD
2012
ACM
232views Database» more  SIGMOD 2012»
11 years 10 months ago
Large-scale machine learning at twitter
The success of data-driven solutions to difficult problems, along with the dropping costs of storing and processing massive amounts of data, has led to growing interest in largesc...
Jimmy Lin, Alek Kolcz
NLPRS
2001
Springer
14 years 1 days ago
A Bayesian Approach to Semi-Supervised Learning
Recent research in automated learning has focused on algorithms that learn from a combination of tagged and untagged data. Such algorithms can be referred to as semi-supervised in...
Rebecca F. Bruce