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» Unsupervised Natural Language Processing Using Graph Models
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ACL
2009
13 years 8 months ago
A Graph-based Semi-Supervised Learning for Question-Answering
We present a graph-based semi-supervised learning for the question-answering (QA) task for ranking candidate sentences. Using textual entailment analysis, we obtain entailment sco...
Asli Çelikyilmaz, Marcus Thint, Zhiheng Hua...
JUCS
2010
213views more  JUCS 2010»
13 years 8 months ago
Mining Feature-Opinion in Online Customer Reviews for Opinion Summarization
: Online customer reviews is considered as a significant informative resource which is useful for both potential customers and product manufacturers. In web pages, the reviews are ...
Gamgarn Somprasertsri, Pattarachai Lalitrojwong
MODELS
2009
Springer
14 years 2 months ago
An Example Is Worth a Thousand Words: Composite Operation Modeling By-Example
Abstract. Predefined composite operations are handy for efficient modeling, e.g., for the automatic execution of refactorings, and for the introduction of patterns in existing mod...
Petra Brosch, Philip Langer, Martina Seidl, Konrad...
UML
2004
Springer
14 years 3 months ago
OCL and Model Driven Engineering
Precise modeling is essential to the success of the OMG’s Model Driven Architecture initiative. At the modeling level (M1) OCL allows for the precision needed to write executable...
Jean Bézivin, Thomas Baar, Tracy Gardner, M...
SIGIR
2008
ACM
13 years 10 months ago
Generating diverse katakana variants based on phonemic mapping
In Japanese, it is quite common for the same word to be written in several different ways. This is especially true for katakana words which are typically used for transliterating ...
Kazuhiro Seki, Hiroyuki Hattori, Kuniaki Uehara