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LREC
2010
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13 years 6 months ago
Predicting Morphological Types of Chinese Bi-Character Words by Machine Learning Approaches
This paper presented an overview of Chinese bi-character words' morphological types, and proposed a set of features for machine learning approaches to predict these types bas...
Ting-Hao Huang, Lun-Wei Ku, Hsin-Hsi Chen
EMNLP
2008
13 years 6 months ago
Automatic Inference of the Temporal Location of Situations in Chinese Text
Chinese is a language that does not have morphological tense markers that provide explicit grammaticalization of the temporal location of situations (events or states). However, i...
Nianwen Xue
EMNLP
2004
13 years 6 months ago
Learning Hebrew Roots: Machine Learning with Linguistic Constraints
The morphology of Semitic languages is unique in the sense that the major word-formation mechanism is an inherently non-concatenative process of interdigitation, whereby two morph...
Ezra Daya, Dan Roth, Shuly Wintner
COLING
2010
12 years 12 months ago
EMMA: A novel Evaluation Metric for Morphological Analysis
We present a novel Evaluation Metric for Morphological Analysis (EMMA) that is both linguistically appealing and empirically sound. EMMA uses a graphbased assignment algorithm, op...
Sebastian Spiegler, Christian Monson
IJCAI
2007
13 years 6 months ago
Simple Training of Dependency Parsers via Structured Boosting
Recently, significant progress has been made on learning structured predictors via coordinated training algorithms such as conditional random fields and maximum margin Markov ne...
Qin Iris Wang, Dekang Lin, Dale Schuurmans