Retrieving Semantically Distant Analogies with Knowledge-Directed Spreading Activation

Techniques that traditionally have been useful for retrieving same domain analogies from small single use knowledge bases such as spreading activation and indexing on selected features are inadequate for retrieving cross domain analogies from large multi use knowledge bases In this paper we describe Knowledge Directed Spreading Activation KDSA a new method for retriev ing analogies in a large semantic network KDSA uses task speci c knowledge to guide a spreading activation search to a case or concept in memory that meets a desired similarity condition Speci cally KDSA exploits evaluations of near analogies encountered during the search to direct the search toward pro gressively more promising analogies We describe a speci c instantiation of this method for the task of innovative design and we summarize the theoretical and experimental results used to validate KDSA