This paper presents Domain Relevance Estimation (DRE), a fully unsupervised text categorization technique based on the statistical estimation of the relevance of a text with respe...
Kernel-based learning (e.g., Support Vector Machines) has been successfully applied to many hard problems in Natural Language Processing (NLP). In NLP, although feature combinatio...
In statistical machine translation, the generation of a translation hypothesis is computationally expensive. If arbitrary wordreorderings are permitted, the search problem is NP-h...
We examine the issues that arise in extending an estimatedregression (ER) planner to reason about autonomous processes that run and have continuous and discrete effects without th...
Expressing web page content in a way that computers can understand is the key to a semantic web. Generating ontological information from the web automatically using machine learni...