We explore a stacked framework for learning to predict dependency structures for natural language sentences. A typical approach in graph-based dependency parsing has been to assum...
In this work we propose an approach of incorporating learned mutation strategies (LMS) in genetic programming (GP) employed for evolution and adaptation of locomotion gaits of sim...
Determining the attachments of prepositions and subordinate conjunctions is a key problem in parsing natural language. This paper presents a trainable approach to making these att...
This paper analyzes the impact of several lexical and grammatical features in automated assessment of students' finegrained understanding of tutored concepts. Truly effective...
We propose an algorithm for extracting fields from HTML search results. The output of the algorithm is a database table– a data structure that better lends itself to high-level...