Lucian Vlad Lita, Abe Ittycheriah
Truecasing is the process of restoring case information to badly-cased or noncased text. This paper explores truecasing issues and proposes a statistical, language modeling based truecaser which...
Lucian Vlad Lita, Abe Ittycheriah
Truecasing is the process of restoring case information to badly-cased or noncased text. This paper explores truecasing issues and proposes a statistical, language modeling based truecaser which...
Lucian Vlad Lita, Abe Ittycheriah
Truecasing is the process of restoring case information to badly-cased or noncased text. This paper explores truecasing issues and proposes a statistical, language modeling based truecaser which...
Lucian Vlad Lita, Abe Ittycheriah, Salim Roukos, Nanda Kambhatla
Truecasing is the process of restoring case information to badly-cased or noncased text. This paper explores truecasing issues and proposes a statistical, language modeling based truecaser which...
A Mention-Synchronous Coreference Resolution Algorithm Based on the Bell Tree (2004)
Xiaoqiang Luo, Abe Ittycheriah, Hongyan Jing, A Kambhatla, Salim Roukos
This paper proposes a new approach for coreference resolution which uses the Bell tree to represent the search space and casts the coreference resolution problem as finding the best path from the...
Named entity recognition through classifier combination (2003)
Radu Florian, Abe Ittycheriah, Hongyan Jing, Tong Zhang
This paper presents a classifier-combination experimental framework for named entity recognition in which four diverse classifiers (robust linear classifier, maximum entropy, transformation-based...
Named entity recognition through classifier combination (2003)
Radu Florian, Abe Ittycheriah, Hongyan Jing, Tong Zhang
This paper presents a classifier-combination experimental framework for named entity recognition in which four diverse classifiers (robust linear classifier, maximum entropy, transformation-based...
Named entity recognition through classifier combination (2003)
Radu Florian, Abe Ittycheriah, Hongyan Jing, Tong Zhang
This paper presents a classifier-combination experimental framework for named entity recognition in which four diverse classifiers (robust linear classifier, maximum entropy, transformation-based...