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Signed Feature Constraint Solving

Jean-Marc Andreoli, Uwe Borghoff, Remo Pareschi
Intelligent brokering of information needs algorithmically tractable knowledge representations and corresponding constraint solvers to tackle the satisfiability problems involved. Feature constraints emerged soon as a convenient and elegant choice of knowledge representation. The full fragment of feature constraints, where sorts and features are allowed to be combined by all the logical connectives (conjunction, disjunction, negation and quantifiers), although very expressive, is hardly tractable. On the other hand, the subfragment called "basic feature constraints" (BFC), where negation and disjunction are simply forbidden, unneccesarily restricts applications such as knowledge brokers in an intolerable way. The main contribution of this paper is twofold. On the one hand, it presents a fragment of feature constraints, called "signed feature constraints" (SFC), which allows limited use of negation, precisely capable of expressing the kind of operations needed during intelligent brokering, and on the other hand, discusses an efficient constraint solving method for SFC. Since early 1996, the SFC solver performs efficiently within the Constraint Based Knowledge Broker system (CBKB). The CBKB system aims at heterogeneous information retrieval, schema integration, and knowledge fusion.
Proc. 3rd Int. Conf. on Practical Application of Constraint Technology (PACT '97), April 23-25, 1997, London, U.K., pp. 35-46


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