20,866 research outputs found

    Alternative approach to tree-structured web log representation and mining

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    More recent approaches to web log data representation aim to capture the user navigational patterns with respect to the overall structure of the web site. One such representation is tree-structured log files which is the focus of this work. Most existing methods for analyzing such data are based on the use of frequent subtree mining techniques to extract frequent user activity and navigational paths. In this paper we evaluate the use of other standard data mining techniques enabled by a recently proposed structure preserving flat data representation for tree-structured data. The initially proposed framework was adjusted to better suit the web log mining task. Experimental evaluation is performed on two real world web log datasets and comparisons are made with an existing state-of-the art classifier for tree-structured data. The results show the great potential of the method in enabling the application of a wider range of data mining/analysis techniques to tree-structured web log data

    Ten virtues of structured graphs

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    This paper extends the invited talk by the first author about the virtues of structured graphs. The motivation behind the talk and this paper relies on our experience on the development of ADR, a formal approach for the design of styleconformant, reconfigurable software systems. ADR is based on hierarchical graphs with interfaces and it has been conceived in the attempt of reconciling software architectures and process calculi by means of graphical methods. We have tried to write an ADR agnostic paper where we raise some drawbacks of flat, unstructured graphs for the design and analysis of software systems and we argue that hierarchical, structured graphs can alleviate such drawbacks

    Mining complex structured data: Enhanced methods and applications

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    Conventional approaches to analysing complex business data typically rely on process models, which are difficult to construct and use. This thesis addresses this issue by converting semi-structured event logs to a simpler flat representation without any loss of information, which then enables direct applications of classical data mining methods. The thesis also proposes an effective and scalable classification method which can identify distinct characteristics of a business process for further improvements

    From treebank resources to LFG F-structures

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    We present two methods for automatically annotating treebank resources with functional structures. Both methods define systematic patterns of correspondence between partial PS configurations and functional structures. These are applied to PS rules extracted from treebanks, or directly to constraint set encodings of treebank PS trees

    Trustworthy Refactoring via Decomposition and Schemes: A Complex Case Study

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    Widely used complex code refactoring tools lack a solid reasoning about the correctness of the transformations they implement, whilst interest in proven correct refactoring is ever increasing as only formal verification can provide true confidence in applying tool-automated refactoring to industrial-scale code. By using our strategic rewriting based refactoring specification language, we present the decomposition of a complex transformation into smaller steps that can be expressed as instances of refactoring schemes, then we demonstrate the semi-automatic formal verification of the components based on a theoretical understanding of the semantics of the programming language. The extensible and verifiable refactoring definitions can be executed in our interpreter built on top of a static analyser framework.Comment: In Proceedings VPT 2017, arXiv:1708.0688

    Automatic F-Structure Annotation from the AP Treebank

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    We present a method for automatically annotating treebank resources with functional structures. The method defines systematic patterns of correspondence between partial PS configurations and functional structures. These are applied to PS rules extracted from treebanks. The set of techniques which we have developed constitute a methodology for corpus-guided grammar development. Despite the widespread belief that treebank representations are not very useful in grammar development, we show that systematic patterns of c-structure to f-structure correspondence can be simply and successfully stated over such rules. The method is partial in that it requires manual correction of the annotated grammar rules
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