Integrated Learning of Words and Their Underlying Concepts

摘要

Models of learning word meanings have generally assumed prior knowledge of the concepts to which the words refer. However, novel natural language text or discourse can often present both unknown concepts and words and their concepts frequently occurs concurrently instead of concept learning proceeding word learning. This paper presents an integrated computational model for acquiring both word meanings and their underlying concepts concurrently. This model is implemented as a word learning component added to the GENESIS explanation-based schema acquisition system for narrative understanding. A detailed example is described in which GENESIS learns provisional definitions for the words kidnap, kidnapper, and ransom as well as a kidnapping schema from a single narrative. Keywords: Explanation-Based Learning, Concept Acquisition.