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CLASSIC: A Structural Data Model for Objects
, 1989
"... CLASSIC is a data model that encourages the description ofobjects not only in terms of their relations to other known objects, but in terms of a level of intensional structure as well. The CLASSIC language of structured descriptions permits i) partial descriptions of individuals, under an `open worl ..."
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Cited by 327 (25 self)
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CLASSIC is a data model that encourages the description ofobjects not only in terms of their relations to other known objects, but in terms of a level of intensional structure as well. The CLASSIC language of structured descriptions permits i) partial descriptions of individuals, under an `open world' assumption, ii) answers to queries either as extensional lists of valuesorasdescriptions that necessarily hold of all possible answers, and iii) an easily extensible schema, which can be accessed uniformly with the data. One of the strengths of the approach is that the same language plays multiple roles in the processes of defining and populating the DB, as well as querying and answering. classic (for which we have a prototype main-memory implementation) can actively discover new information about objects from several sources: it can recognize new classes under which an object falls based on a description of the object, it can propagate some deductive consequences of DB upda...
A Softbot-Based Interface to the Internet
- Communications of the ACM
, 1994
"... this article, we focus on the ideas underlying the softbot-based interface. ..."
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Cited by 263 (18 self)
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this article, we focus on the ideas underlying the softbot-based interface.
The Alternating Fixpoint of Logic Programs with Negation
, 1995
"... The alternating fixpoint of a logic program with negation is defined constructively. The underlying idea is monotonically to build up a set of negative conclusions until the least fixpoint is reached, using a transformation related to the one that defines stable models. From a fixed set of negative ..."
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Cited by 189 (2 self)
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The alternating fixpoint of a logic program with negation is defined constructively. The underlying idea is monotonically to build up a set of negative conclusions until the least fixpoint is reached, using a transformation related to the one that defines stable models. From a fixed set of negative conclusions, the positive conclusions follow (without deriving any further negative ones), by traditional Horn clause semantics. The union of positive and negative conclusions is called the alternating xpoint partial model. The name "alternating" was chosen because the transformation runs in two passes; the first pass transforms an underestimate of the set of negative conclusions into an (intermediate) overestimate; the second pass transforms the overestimate into a new underestimate; the composition of the two passes is monotonic. The principal contributions of this work are (1) that the alternating fixpoint partial model is identical to the well-founded partial model, and (2) that alternating xpoint logic is at least as expressive as xpoint logic on all structures. Also, on finite structures, fixpoint logic is as expressive as alternating fixpoint logic.
Inconsistency Handling in Multi-Perspective Specifications
- IEEE TRANSACTIONS ON SOFTWARE ENGINEERING
, 1994
"... The development of most large and complex systems necessarily involves many people - each with their own perspectives on the system defined by their knowledge, responsibilities, and commitments. To address this we have advocated distributed development of specifications from multiple perspectives. ..."
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Cited by 171 (41 self)
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The development of most large and complex systems necessarily involves many people - each with their own perspectives on the system defined by their knowledge, responsibilities, and commitments. To address this we have advocated distributed development of specifications from multiple perspectives. However, this leads to problems of identifying and handling inconsistencies between such perspectives. Maintaining absolute consistency is not always possible. Often this is not even desirable since this can unnecessarily constrain the development process, and can lead to the loss of important information. Indeed since the real-world forces us to work with inconsistencies, we should formalise some of the usually informal or extra-logical ways of responding to them. This is not necessarily done by eradicating inconsistencies but rather by supplying logical rules specifying how we should act on them. To achieve this, we combine two lines of existing research: the ViewPoints framew...
Logic and databases: a deductive approach
- ACM Computing Surveys
, 1984
"... The purpose of this paper is to show that logic provides a convenient formalism for studying classical database problems. There are two main parts to the paper, devoted respectively to conventional databases and deductive databases. In the first part, we focus on query languages, integrity modeling ..."
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Cited by 130 (2 self)
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The purpose of this paper is to show that logic provides a convenient formalism for studying classical database problems. There are two main parts to the paper, devoted respectively to conventional databases and deductive databases. In the first part, we focus on query languages, integrity modeling and maintenance, query optimization, and data
Sound and efficient closed-world reasoning for planning
- Artificial Intelligence
, 1997
"... Closed-world inference is the process of determining that a logical sentence is false based on its absence from a knowledge base, or the inability to derive it. This process is essential for planning with incomplete information. We describe a novel method for closed-world inference and update over t ..."
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Cited by 65 (12 self)
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Closed-world inference is the process of determining that a logical sentence is false based on its absence from a knowledge base, or the inability to derive it. This process is essential for planning with incomplete information. We describe a novel method for closed-world inference and update over the first-order theories of action used by planning algorithms such as NONLIN, TWEAK, and UCPOP. We show the method to be sound and efficient, but incomplete. In our experiments, closed-world inference consistently averaged about 2 milliseconds, while updates averaged approximately 1.2 milliseconds. We incorporated the method into the XII planner, which supports our Internet Softbot (software robot). The method cut the number of actions executed by the Softbot bya factor of one hundred, and resulted in a corresponding speedup to XII. 1
Fuzzy functional dependencies and lossless join decomposition of fuzzy relational database systems
- ACM Transactions on Database Systems
, 1988
"... This paper deals with the application of fuzzy logic in a relational database environment with the objective of capturing more meaning of the data. It is shown that with suitable interpretations for the fuzzy membership functions, a fuzzy relational data model can be used to represent ambiguities in ..."
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Cited by 65 (0 self)
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This paper deals with the application of fuzzy logic in a relational database environment with the objective of capturing more meaning of the data. It is shown that with suitable interpretations for the fuzzy membership functions, a fuzzy relational data model can be used to represent ambiguities in data values as well as impreciseness in the association among them. Relational operators for fuzzy relations have been studied, and applicability of fuzzy logic in capturing integrity constraints has been investigated. By introducing a fuzzy resemblance measure EQUAL for comparing domain values, the definition of classical functional dependency has been generalized to fuzzy functional dependency (ffd). The implication problem of ffds has been examined and a set of sound and complete inference axioms has been proposed. Next, the problem of lossless join decomposition of fuzzy relations for a given set of fuzzy functional dependencies is investigated. It is proved that with a suitable restriction on EQUAL, the design theory of a classical relational database with functional dependencies can be extended to fuzzy relations satisfying fuzzy functional dependencies.
On the Semantics of Theory Change: Arbitration between Old and New Information
- In Proceedings of the Twelfth ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Databases
, 1993
"... : Katsuno and Mendelzon divide theory change, the problem of adding new information to a logical theory, into two types: revision and update. We propose a third type of theory change: arbitration. The key idea is the following: the new information is considered neither better nor worse than the old ..."
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Cited by 48 (0 self)
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: Katsuno and Mendelzon divide theory change, the problem of adding new information to a logical theory, into two types: revision and update. We propose a third type of theory change: arbitration. The key idea is the following: the new information is considered neither better nor worse than the old information represented by the logical theory. The new information is simply one voice against a set of others already incorporated into the logical theory. From this follows that arbitration should be commutative. First we define arbitration by a set of postulates and then describe a model-theoretic characterization of arbitration for the case of propositional logical theories. We also study weighted arbitration where different models of a theory can have different weights. 1 Introduction The problem of updating logical theories is a common fundamental concern to databases, to Artificial Intelligence [McC68, Rei92], and to belief revision [Mak85, Gar88]. It is well-known that giving semant...
Reasoning about naming systems
- ACM Transactions on Programming Languages and Systems
, 1993
"... This paper reasons about naming systems as specialized inference mechanisms, It describes a preference)-zierarch.v that can be used to specify the structure of a naming system’s inference mechanism and defines criteria by which different naming systems can be evaluated, For example, the preference h ..."
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Cited by 39 (1 self)
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This paper reasons about naming systems as specialized inference mechanisms, It describes a preference)-zierarch.v that can be used to specify the structure of a naming system’s inference mechanism and defines criteria by which different naming systems can be evaluated, For example, the preference hierarchy allows one to compare naming systems based on how dkcrzmznating they are and to identify the class of names for which a given naming system is sound and complete. A study of several example naming systems demonstrates how the prefer-ence hierarchy can be used as a formal tool for designing naming systems. Categories and Subject Descriptors: H.2.3 [Database Management]: Languages—query lan-guages; H.2.4 [Database Management]: Systems—query processing; H.3.3 [Information

