Building Thematic Lexical Resources by Bootstrapping and Machine Learning
Alberto Lavelli, Bernardo Magnini, Fabrizio Sebastiani · 2002
We discuss work in progress in the semi-automatic generation of thematic lexicons by means of term categorization, a novel task employing techniques from information retrieval (IR) and machine learning (ML). Specifically, we view the generation of such lexicons as an iterative process of learning previously unknown associations between terms and themes (i.e. disciplines, or fields of activity). The process is iterative, in that it generates, for each c i in a set C = {c1,...,c m} of themes, a sequence L ...