We propose a novel method to automatically acquire a term-frequency-based taxonomy from a corpus using an unsupervised method. A term-frequency-based taxonomy is useful for applic...
Karin Murthy, Tanveer A. Faruquie, L. Venkata Subr...
The main focus of this work is to investigate robust ways for generating summaries from summary representations without recurring to simple sentence extraction and aiming at more ...
Josef Steinberger, Marco Turchi, Mijail Alexandrov...
We evaluate the effect of adding parse features to a leading model of preposition usage. Results show a significant improvement in the preposition selection task on native speaker...
Joel R. Tetreault, Jennifer Foster, Martin Chodoro...
We demonstrate that transformation-based learning can be used to correct noisy speech recognition transcripts in the lecture domain with an average word error rate reduction of 12...
To address semantic ambiguities in coreference resolution, we use Web n-gram features that capture a range of world knowledge in a diffuse but robust way. Specifically, we exploi...