By Cristhian A. D. Deagustini, Santiago E. Fulladoza Dalibón, Sebastián Gottifredi (auth.), Stephen W. Liddle, Klaus-Dieter Schewe, A Min Tjoa, Xiaofang Zhou (eds.)

This quantity set LNCS 7446 and LNCS 7447 constitutes the refereed complaints of the twenty third overseas convention on Database and professional platforms functions, DEXA 2012, held in Vienna, Austria, September 3-6, 2012.
The forty nine revised complete papers provided including 37 brief papers and a couple of keynote talks have been rigorously reviewed and chosen from 179 submissions. those papers talk about various themes together with: database question processing, specifically XML queries; labelling of XML records; computational potency, info extraction; personalization, personal tastes, and rating; safety and privateness; database schema review and evolution; semantic internet; privateness and provenance; info mining; information streaming; disbursed platforms; looking out and question answering; structuring, compression and optimization; failure, fault research, and uncertainty; predication, extraction, and annotation; score and personalisation; database partitioning and function size; suggestion and prediction structures; company techniques; social networking.

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Additional info for Database and Expert Systems Applications: 23rd International Conference, DEXA 2012, Vienna, Austria, September 3-6, 2012. Proceedings, Part II

Sample text

For this purpose, we introduce two components in the scientific knowledge discovery pipeline, the lossless compressor and query engine. 20 J. Jenkins et al. 2 Compression Scientific simulations use predominantly double-precision floating-point variables, so the remainder of the paper will focus on compression and query processing for these variables, though our method can be applied to variables of different precision. The underlying representation of these variables, using the IEEE 754 floating-point standard [1], is a primary driver of our compression and querying methodology, so we briefly review it here.

Instead, we use a subset of Σ formed only by presumptions needed to build arguments in the d-tree of the queried literal. Regarding disagreement and defeat relations between arguments in DBI-DeLP, we will use the notions of proper and blocking defeaters defined just like in [7]. Nevertheless, to determine which argument prevails when two arguments disagree in DBI-DeLP we will use a combination of the generalized specificity comparison criterion introduced earlier with an additional comparison criterion that will be used to define the preference of data coming from some available databases over others.

Pn is a list of the predicate’s parameters (e. , for genre(commando, Genre) its functor is genre while commando and Genre are its parameters). D. Deagustini et al. The SLD procedure will try to prove every Function Objective using all rules, facts and presumptions in the DBI-DeLP program; but for the purpose of this section we will focus on how presumptions can be obtained from databases. To do this, a search for presumptions is launched (see condition (a) of Def. 1), in order to retrieve from the databases, if exists, some information offering support to the literal.

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