Efficient question answering in a hybrid system

Abstract

A connectionist model for answering open-class questions in the context of text processing is presented. The system answers questions from different question categories, such as how, why, and consequence questions. The system responds to a question by generating a set of possible answers that are weighted according to their plausibility. Search is performed by means of a massively parallel directed spreading activation process. The search process operates on several knowledge sources (i.e., connectionist networks) that are learned or explicitly built-in. Spreading activation involves the use of signature messages, which are numeric values that are propagated throughout the networks and identify a particular question category (this makes the system hybrid). Binder units that gate the flow of activation between textual units receive these signatures and change their states. That is, the binder units either block the spread of activation or allow the flow of activation in a certain direction. The process results in a pattern of activation that represents a set of candidate answers based on available knowledge sources.<>