Classification as a query processing technique in the CANDIDE semantic data model

Abstract

The use of classification and subsumption to process database queries is discussed. The data model, called CANDIDE, is essentially an extended version of the FL-1, KANDOR and BACK, frame-based knowledge representation languages. A novel feature of the approach is that the data-description language and data-manipulation language are identical, thus providing uniform treatment of data objects, query objects and view objects. The classification algorithm find the correct placement for a query object in a given object taxonomy. Tractability issues are explored, and the expressiveness of queries is compared with relational algebra. This data model has been implemented in POPLOG as the basis for a knowledge-base management system that includes an integrated natural-language query system.<>