By Morzy Tadeusz, Patrick Valduriez, Ladjel Bellatreche
This publication constitutes the completely refereed court cases of the nineteenth East eu 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 conscientiously chosen and reviewed from a hundred thirty five submissions. The papers are equipped in topical sections reminiscent of database thought 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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Additional info for Advances in Databases and Information Systems: 19th East European Conference, ADBIS 2015, Poitiers, France, September 8-11, 2015, Proceedings
1 27 Performance in Similarity Queries This subsection presents the results comparing the performance of Slim-tree + CLAP and ACIR with the original Slim-tree to execute similarity queries. In these experiments, k-NN queries and Range queries were performed varying the k value (1, 10, 25, 50, 100, 150, 200, 250 and 300) and using the corresponding radius values to retrieve k elements in Range queries. For each k, the results were obtained by performing queries multiple times (500 when using the L2 metric and 100 when using the Mahalanobis metric), each time with a random query element, and taking the average value.
Edu/ml 4. : Conditional functional dependencies for data cleaning. In: 23rd ICDE, pp. 746–755 (2007) 5. : Extending dependencies with conditions. In: 33rd International Conference on VLDB, pp. 243–254 (2007) 6. : Analyses and validation of conditional dependencies with built-in predicates. , Wagner, R. ) DEXA 2009. LNCS, vol. 5690, pp. 576–591. Springer, Heidelberg (2009) 7. : Foundations of Data Quality Management. Synth. Lect. Data Manage. 4(5), 1–127 (2012). 2200/S00439ED1V01Y201207DTM030 8.
This allows avoiding unnecessary disk accesses in situations like the one depicted in Fig. 2, where the child node centered in s1 intercepts the search region deﬁned by sq , but none of its children — s11 , s12 , s13 and s14 , which are grandchild nodes of the current node (the biggest one, centered in srep ) — intercepts the uncertainty region represented by the dashed ring within the child node centered in s1 . The evaluation of whether the grandchild nodes intercept or not this uncertainty region can happen in the current level only because their distances and radii have been anticipated.