The centering framework explains local coherence by relating local focus and the form of referring expressions. It has proven useful in monolog, but its utility for multiparty dis...
The noisy channel model has been applied to a wide range of problems, including spelling correction. These models consist of two components: a source model and a channel model. Ve...
This study exploits statistical redundancy inherent in natural language to automatically predict scores for essays. We use a hybrid feature identification method, including syntac...
Jill Burstein, Karen Kukich, Susanne Wolff, Chi Lu...
We present an LFG-DOP parser which uses fragments from LFG-annotated sentences to parse new sentences. Experiments with the Verbmobil and Homecentre corpora show that (1) Viterbi ...
This paper describes a new scoring algorithm that supports comparison of linguistically annotated data from noisy sources. The new algorithm generalizes the Message Understanding ...
John D. Burger, David D. Palmer, Lynette Hirschman
This paper introduces a statistical model for query-relevant summarization: succinctly characterizing the relevance of a document to a query. Learning parameter values for the pro...
This paper presents a technique to deal with multiword nominal terminology in a computational Lexical Functional Grammar. This method treats multiword terms as single tokens by mo...
This paper proposes decoupling the dependency tree from word order, such that surface ordering is not determined by traversing the dependency tree. We develop the notion of a word...
One of the most exciting recent directions in machine learning is the discovery that the combination of multiple classifiers often results in significantly better performance than...
Extractive summarization techniques cannot generate document summaries shorter than a single sentence, something that is often required. An ideal summarization system would unders...
Michele Banko, Vibhu O. Mittal, Michael J. Witbroc...