Most topic models, such as latent Dirichlet allocation, rely on the bag-of-words assumption. However, word order and phrases are often critical to capturing the meaning of text in...
Semantic taxonomies such as WordNet provide a rich source of knowledge for natural language processing applications, but are expensive to build, maintain, and extend. Motivated by...
Knowledge-based natural language processing systems learn by reading, i.e., they process texts to extract knowledge. The performance of these systems crucially depends on knowledg...
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...
—We present the STORIES methods and tool for (a) an abstracted story representation from a collection of time-indexed documents; (b) visualising it in a way that encourages users...