Various text mining algorithms require the process of feature selection. High-level semantically rich features, such as figurative language uses, speech errors etc., are very prom...
We present the S-Space Package, an open source framework for developing and evaluating word space algorithms. The package implements well-known word space algorithms, such as LSA,...
We present a novel fully unsupervised algorithm for POS induction from plain text, motivated by the cognitive notion of prototypes. The algorithm first identifies landmark cluster...
This paper describes the application of so-called topic models to selectional preference induction. Three models related to Latent Dirichlet Allocation, a proven method for modell...
We explore how to improve machine translation systems by adding more translation data in situations where we already have substantial resources. The main challenge is how to buck ...