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dc.contributor.authorLee, Jintae
dc.date.accessioned2008-04-28T14:33:32Z
dc.date.available2008-04-28T14:33:32Z
dc.date.issued1985-08
dc.identifier.urihttp://hdl.handle.net/1721.1/41485
dc.description.abstractIn this paper, an intelligent database management system (DBMS) called IDEME is presented. IDEME is a program that takes as input a task specification and finds a set of methods potentially relevant to solving that task. It does so by matching the task specification to the methods in its database at multiple levels of abstraction. After isolating potentially useful methods, IDEME ranks them by how relevant they might be to the task. From the most relevant method, it checks if its operational demands, i.e. those conditions that have to be satisfied for the method to be applicable, are satisfied by the present task. If so, it presents the algorithm of the method relativized to the present task; otherwise, it goes on to the next method. In this paper, the focus will be on the representation scheme that is used by IDEME to represent methods as well as tasks.en
dc.description.sponsorshipMIT Artificial Intelligence Laboratoryen
dc.language.isoen_USen
dc.publisherMIT Artificial Intelligence Laboratoryen
dc.relation.ispartofseriesMIT Artificial Intelligence Laboratory Working Papers, WP-276en
dc.titleIDEME: A DBMS of Methodsen
dc.typeWorking Paperen


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