By Morzy Tadeusz, Patrick Valduriez, Ladjel Bellatreche
This ebook constitutes the completely refereed lawsuits of the nineteenth East ecu convention on Advances in Databases and data structures, ADBIS 2015, held in Poitiers, France, in September 2015. The 31 complete papers and 18 brief papers provided have been rigorously chosen and reviewed from a hundred thirty five submissions. The papers are geared up in topical sections comparable to database concept and entry tools; consumer necessities and database evolution; multidimensional modeling and OLAP; ETL; transformation, extraction and archiving; modeling and ontologies; time sequence processing; functionality and tuning; complicated question processing; approximation and skyline; confidentiality and trust.
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Extra resources for Advances in Databases and Information Systems: 19th East European Conference, ADBIS 2015, Poitiers, France, September 8-11, 2015, Proceedings
They are presented in the next sections. 3 The CLAP Technique This section describes our new technique to improve the pruning ability of dynamic MAMs, named Cutting Local Additional Pivots (CLAP). It aims at reducing the uncertainty region of each node accessed in a similarity query. However, distinctly from other strategies that employ multiple local pivots, in which the pivots deﬁne the covering region of a node, as in the MM-tree and the Onion-tree, the CLAP technique is used to cut the region deﬁned by a node representative applying the triangular inequality pruning mechanism using local additional pivots.
The amsterdam library of object images. Int. J. Comput. Vis. 61(1), 103–112 (2005) 11. : The MM-tree: a memory-based metric tree without overlap between nodes. , Rachev, B. ) ADBIS 2007. LNCS, vol. 4690, pp. 157–171.
Consistency Analysis of CDDs: A set Σ of CDDs is said to be consistent if there exists an instance r of R that has at least two tuples (ALTT) and that satisﬁes Σ. The consistency problem C is to determine the existence of an ALTT instance for a given set Σ of CDDs. C is NP-complete for DDs ; and CDDs maintain the same complexity. Theorem 1. The consistency problem for CDDs is NP-complete. Proof. The NP-hard bound follows the NP-hardness of C for DDs, a special case of CDDs. NP bound is veriﬁed by an NP algorithm that can decide if r |= Σ.