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IJAR
2006
89views more  IJAR 2006»
15 years 4 months ago
Learning probabilistic decision graphs
Probabilistic decision graphs (PDGs) are a representation language for probability distributions based on binary decision diagrams. PDGs can encode (context-specific) independence...
Manfred Jaeger, Jens D. Nielsen, Tomi Silander
OTM
2010
Springer
15 years 2 months ago
A Personalized and Collaborative eLearning Materials Recommendation Scenario Using Ontology-Based Data Matching Strategies
Abstract. We propose a virtual teacher for the evaluation of students’ competencies. It aims to improve learning by making personalized suggestions on the learning materials. It ...
Ioana Ciuciu, Yan Tang
NAACL
2010
15 years 2 months ago
Taxonomy Learning Using Word Sense Induction
Taxonomies are an important resource for a variety of Natural Language Processing (NLP) applications. Despite this, the current stateof-the-art methods in taxonomy learning have d...
Ioannis P. Klapaftis, Suresh Manandhar
145
Voted
NAACL
2010
15 years 2 months ago
Learning Words and Their Meanings from Unsegmented Child-directed Speech
Most work on language acquisition treats word segmentation--the identification of linguistic segments from continuous speech-and word learning--the mapping of those segments to me...
Bevan K. Jones, Mark Johnson, Michael C. Frank
ICTAI
2008
IEEE
15 years 10 months ago
Classifying Spend Descriptions with Off-the-Shelf Learning Components
Analyzing spend transactions is essential to organizations for understanding their global procurement. Central to this analysis is the automated classification of these transacti...
Saikat Mukherjee, Dmitriy Fradkin, Michael Roth