Automatically categorizing documents into pre-defined topic hierarchies or taxonomies is a crucial step in knowledge and content management. Standard machine learning techniques ...
This work relates to the implementation of a 2D conditional random field model in the context of document image analysis. Our model makes it possible to take variability into acco...
A pervasive problem in large relational databases is identity uncertainty which occurs when multiple entries in a database refer to the same underlying entity in the world. Relati...
Systems based on statistical and machine learning methods have been shown to be extremely effective and scalable for the analysis of large amount of textual data. However, in the r...
We address the problem of advice-taking in a given domain, in particular for building a game-playing program. Our approach to solving it strives for the application of machine lea...