Automated acquisition of rules for document understanding

A study on the possibility of adopting a supervised inductive learning approach to the problem of document understanding is presented. A representation language used to describe a page layout is introduced and the opportunity of extending such a language by means of intentionally defined predicates is discussed. Experimental results obtained by using a well-known learning system, FOCL, are presented. They confirm the exigency of redefining the problem of document understanding in terms of a new strategy of supervised inductive learning, called contextual learning. Some experiments in which a dependence hierarchy between concepts is defined show that contextual rules increase predictive accuracy and decrease learning time for labeling problems like document understanding