Spontaneous Retrieval in a Conceptual Information System

Abstract

A traditional paradigm for retrieval from a conceptual knowledge base is to gather up indices or features used to discriminate among or locate items in memory, and then perform a retrieval operation to obtain matching items. These items may then be evaluated for their degree of match against the input. This type of approach to retrieval has some problems. It requires one to look explicitly for items in memory whenever the possibility exists that there might be something of interest there. Also, this approach does not easily tolerate discrepancies or omissions in the input features or indices. In a question-answering system, a user may make incorrect assumptions about the contents of the knowledge base. This makes a tolerant retrieval method even more necessary. An alternative, two-stage model of conceptual information retrieval is proposed. The first stage is a spontaneous retrieval that operates by a simpie markerpassing scheme. It is spontaneous because items are retrieved as a by-product of the input understanding process. The second stage is a graph matching process that filters and evaluates items retrieved by the first stage. This scheme has been implemented and validated in the SCISOR information retrieval system.