Extracting Viewpoints from Multifunctional Knowledge Bases.

摘要

Viewpoints are coherent collections of facts that describe a concept from a particular perspective. They are essential for a wide variety of tasks, such as explanation generation and qualitative modeling. We have identified many types of viewpoints and developed a program, the View Retriever, for extracting them from knowledge bases, either singly or in combinations. The View Retriever provides a general solution to the central problem in extracting viewpoints: determining which facts are relevant to requested viewpoints. Our evaluation of the View Retriever indicates that it provides most of the types of viewpoints that people use, and its viewpoints are comparable in coherence to those constructed by people. Artificial intelligence, Intelligent tutoring systems, Computer-based instruction, Training.