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Andrea Pugliese
Researcher at University of Calabria
Publications - 120
Citations - 2091
Andrea Pugliese is an academic researcher from University of Calabria. The author has contributed to research in topics: Operational amplifier & XML. The author has an hindex of 26, co-authored 118 publications receiving 2016 citations. Previous affiliations of Andrea Pugliese include National Research Council & Indian Council of Agricultural Research.
Papers
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Journal ArticleDOI
Distributed data mining on grids: services, tools, and applications
TL;DR: The paper discusses how to design and implement data mining applications by using the KNOWLEDGE GRID tools starting from searching grid resources, composing software and data components, and executing the resulting data mining process on a grid.
Journal ArticleDOI
Fast detection of XML structural similarity
TL;DR: In this paper, an approach for detecting structural similarity between XML documents which significantly differs from standard methods based on graph-matching algorithms, and allows a significant reduction of the required computation costs.
Proceedings Article
GRIN: a graph based RDF index
TL;DR: GRIN outperforms Jena, Sesame and RDFBroker on all three measures for graph based queries (for other types of queries, it may be worth building one of these other indexes and using it), at the expense of using a larger amount of memory when answering queries.
Proceedings Article
Detecting Structural Similarities between XML Documents.
TL;DR: The technique is based on the idea of representing the structure of an XML document as a time series in which each occurrence of a tag corresponds to a given impulse by analyzing the frequencies of the corresponding Fourier transform.
Proceedings ArticleDOI
Scaling RDF with Time
TL;DR: This paper proposes the tGRIN index structure that builds a specialized index for temporal RDF that is physically stored in an RDBMS, and shows that even when these efforts are augmented with well known temporal indexes like R+ trees, SR-trees, ST-index, and MAP21, the t GRIN index exhibits superior performance.