6,125 research outputs found

    The use of data-mining for the automatic formation of tactics

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    This paper discusses the usse of data-mining for the automatic formation of tactics. It was presented at the Workshop on Computer-Supported Mathematical Theory Development held at IJCAR in 2004. The aim of this project is to evaluate the applicability of data-mining techniques to the automatic formation of tactics from large corpuses of proofs. We data-mine information from large proof corpuses to find commonly occurring patterns. These patterns are then evolved into tactics using genetic programming techniques

    Automatic Derivation of Abstract Semantics From Instruction Set Descriptions

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    Abstracted semantics of instructions of processor-based architectures are an invaluable asset for several formal verification techniques, such as software model checking and static analysis. In the field of model checking, abstract versions of instructions can help counter the state explosion problem, for instance by replacing explicit values by symbolic representations of sets of values. Similar to this, static analyses often operate on an abstract domain in order to reduce complexity, guarantee termination, or both. Hence, for a given microcontroller, the task at hand is to find such abstractions. Due to the large number of available microcontrollers, some of which are even created for specific applications, it is impracticable to rely on human developers to perform this step. Therefore, we propose a technique that starts from imperative descriptions of instructions, which allows to automate most of the process

    ODEDialect: a set of declarative languages for implementing ontology translation systems

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    Implementing ontology translation systems is a complex task that requires taking many types of translation decisions, which are usually hidden inside their source code. In order to ease building, maintaining and understanding ontology translation systems, we propose ODEDialect, a set of languages to express translation decisions declaratively and at different layers: lexical, syntax, semantics, and pragmatics. This paper describes the three languages that comprise ODEDialect: ODELex, which allows expressing transformations in the lexical layer; ODESyntax, which allows expressing transformations in the syntax layer; and ODESem, which allows expressing transformations in the semantic and pragmatic layers

    Using Ontologies for the Design of Data Warehouses

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    Obtaining an implementation of a data warehouse is a complex task that forces designers to acquire wide knowledge of the domain, thus requiring a high level of expertise and becoming it a prone-to-fail task. Based on our experience, we have detected a set of situations we have faced up with in real-world projects in which we believe that the use of ontologies will improve several aspects of the design of data warehouses. The aim of this article is to describe several shortcomings of current data warehouse design approaches and discuss the benefit of using ontologies to overcome them. This work is a starting point for discussing the convenience of using ontologies in data warehouse design.Comment: 15 pages, 2 figure
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