Bootstrapping semantics from text is one of the greatest challenges in natural language learning. We first define a word similarity measure based on the distributional pattern of ...
Bagging and boosting, two effective machine learning techniques, are applied to natural language parsing. Experiments using these techniques with a trainable statistical parser ar...
We present a model for data organized as graphs. Regular expressions over the types of the node and edge labels are used to qualify connected subgraphs. An algebraic language base...
This paper describes the architecture of a Bulgarian–Bulgarian question answering system — BulQA. The system relies on a partially parsed corpus for answer extraction. The que...
Many sequence labeling tasks in NLP require solving a cascade of segmentation and tagging subtasks, such as Chinese POS tagging, named entity recognition, and so on. Traditional p...