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» Unsupervised Cross-Domain Word Representation Learning
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ACL
2012
11 years 7 months ago
Improving Word Representations via Global Context and Multiple Word Prototypes
Unsupervised word representations are very useful in NLP tasks both as inputs to learning algorithms and as extra word features in NLP systems. However, most of these models are b...
Eric H. Huang, Richard Socher, Christopher D. Mann...
LREC
2008
174views Education» more  LREC 2008»
13 years 6 months ago
UnsuParse: unsupervised Parsing with unsupervised Part of Speech Tagging
Based on simple methods such as observing word and part of speech tag co-occurrence and clustering, we generate syntactic parses of sentences in an entirely unsupervised and self-...
Christian Hänig, Stefan Bordag, Uwe Quasthoff
EMNLP
2008
13 years 6 months ago
Acquiring Domain-Specific Dialog Information from Task-Oriented Human-Human Interaction through an Unsupervised Learning
We describe an approach for acquiring the domain-specific dialog knowledge required to configure a task-oriented dialog system that uses human-human interaction data. The key aspe...
Ananlada Chotimongkol, Alexander I. Rudnicky
ACL
2011
12 years 8 months ago
From Bilingual Dictionaries to Interlingual Document Representations
Mapping documents into an interlingual representation can help bridge the language barrier of a cross-lingual corpus. Previous approaches use aligned documents as training data to...
Jagadeesh Jagarlamudi, Hal Daumé III, Ragha...
BC
2002
90views more  BC 2002»
13 years 4 months ago
What can the hippocampal representation of environmental geometry tell us about Hebbian learning?
The importance of the hippocampus in spatial representation is well established. It is suggested that the rodent hippocampal network should provide an optimal substrate for the stu...
Colin Lever, Neil Burgess, Francesca Cacucci, Tom ...