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Learning Abbreviations from Chinese and English Terms by Modeling Non-Local Information
Xu Sun, Naoaki Okazaki, Jun’ichi Tsujii, Houfeng Wang
Article No.: 5
The present article describes a robust approach for abbreviating terms. First, in order to incorporate non-local information into abbreviation generation tasks, we present both implicit and explicit solutions: the latent variable model and the...
Despite being spoken by a large percentage of the world, Indic languages in general lack user-friendly and efficient methods for text input. These languages have poor or no support for typing. Soft keyboards, because of their ease of installation...
Word Sense Disambiguation by Combining Labeled Data Expansion and Semi-Supervised Learning Method
Sanae Fujita, Akinori Fujino
Article No.: 7
Lack of labeled data is one of the severest problems facing word sense disambiguation (WSD). We overcome the problem by proposing a method that combines automatic labeled data expansion (Step 1) and semi-supervised learning (Step 2). The Step 1...