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Causal Reconstruction

dc.date.accessioned2004-10-04T14:16:02Z
dc.date.accessioned2018-11-24T10:11:16Z
dc.date.available2004-10-04T14:16:02Z
dc.date.available2018-11-24T10:11:16Z
dc.date.issued1993-02-01en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/5955
dc.identifier.urihttp://repository.aust.edu.ng/xmlui/handle/1721.1/5955
dc.description.abstractCausal reconstruction is the task of reading a written causal description of a physical behavior, forming an internal model of the described activity, and demonstrating comprehension through question answering. T his task is difficult because written d escriptions often do not specify exactly how r eferenced events fit together. This article (1) ch aracterizes the causal reconstruction problem, (2) presents a representation called transition space, which portrays events in terms of "transitions,'' or collections of changes expressible in everyday language, and (3) describes a program called PATHFINDER, which uses the transition space representation to perform causal reconstruction on simplified English descriptions of physical activity.en_US
dc.format.extent61 p.en_US
dc.format.extent548466 bytes
dc.format.extent2780985 bytes
dc.language.isoen_US
dc.subjectknowledge representationen_US
dc.subjectexplanationen_US
dc.subjectcausal reasoningen_US
dc.subjectsanalogyen_US
dc.subjectabstractionen_US
dc.subjectnatural languageen_US
dc.titleCausal Reconstructionen_US


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