A new approach for words reordering based on statistical language model

By T. Athanaselis, S. Bakamidis, I. Dologlou. 2006

Subfields: Natural Language Processing, Machine Translation

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Natural Language Processing

1. Maxwell Forbes
2. Luke S. Zettlemoyer
3. Maya Cakmak
4. Yejin Choi
5. Kareem Darwish
6. Hamdy Mubarak
7. Ahmed Abdelali
8. Hannaneh Hajishirzi

In Machine Translation

1. Kareem Darwish
2. Hamdy Mubarak
3. Ahmed Abdelali
4. Luke S. Zettlemoyer

Citations in the corpus

• Robot Programming by Demonstration with situated spatial language understanding (2015, background): “Other work exists that incorporates syntactic [17] or even semantic parsing [4] in creating instructions.”
• Using Stem-Templates to Improve Arabic POS and Gender/Number Tagging (2014, methodology): “Lee et al. (2003) developed IBM-LM, which adopted a trigram language model (LM) trained on a portion of the manually segmented Penn Arabic Treebank (PATB) in developing an Arabic morphology system, which attempts to improve the coverage and linguistic correctness over existing statistical analyzers…”