We propose a latent variable model to enhance historical analysis of large corpora. This work extends prior work in topic modelling by incorporating metadata, and the interactions...
William Yang Wang, Elijah Mayfield, Suresh Naidu, ...
This poster presentation introduces our first Squeak workshops offered in the context of the ALAN-K (Advanced LeArning Network in Kyoto) project (Konomi and Karuno, 2003), which i...
We present a method for improving word alignment for statistical syntax-based machine translation that employs a syntactically informed alignment model closer to the translation m...
Using data from an existing pre-algebra computer-based tutor, we analyzed the covariance of item-types with the goal of describing a more effective way to assign skill labels to it...
Philip I. Pavlik, Hao Cen, Lili Wu, Kenneth R. Koe...
We describe techniques for combining two types of knowledge systems: expert and machine learning. Both the expert system and the learning system represent information by logical d...