By Leonardo Andrade Ribeiro, Theo Härder (auth.), Tadeusz Morzy, Theo Härder, Robert Wrembel (eds.)
This publication constitutes the completely refereed lawsuits of the sixteenth East-European convention on Advances in Databases and data platforms (ADBIS 2012), held in Poznan, Poland, in September 2012. The 32 revised complete papers offered have been conscientiously chosen and reviewed from 122 submissions. The papers disguise a large spectrum of matters about the sector of database and knowledge platforms, together with database conception, database architectures, question languages, question processing and optimization, layout equipment, information integration, view choice, nearest-neighbor looking out, analytical question processing, indexing and caching, concurrency keep watch over, allotted platforms, information mining, facts streams, ontology engineering, social networks, multi-agent platforms, enterprise method modeling, wisdom administration, and application-oriented themes like RFID, XML, and information at the Web.
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Additional resources for Advances in Databases and Information Systems: 16th East European Conference, ADBIS 2012, Poznań, Poland, September 18-21, 2012. Proceedings
Andruszkiewicz the retention replacement randomisation-based method used in the process are known. Hence, the matrix P and values of the attribute C can be computed. , k, where Z is a continuous attribute after distortion and Ii is the i-th interval which corresponds to vi value. These probabilities can be computed for the retention replacement perturbation as follows. , k values of a nominal attribute. Let p be the probability that an original value of a continuous attribute is kept. In the retention replacement perturbation, the probability p does not depend on x, the given value of the attribute X, as well as the probability P (Z ∈ Ii |R ), where R means we change an original value x of the continuous attribute X during the distortion and R states that we retain an original value x for the continuous attribute Z.
For nominal attributes, the probability threshold pthr was set as equal to the probability that an original value would be retained. For continuous attributes the probability threshold pthr was chosen arbitrarily. As a decision tree, we used SPRINT  modiﬁed to incorporate privacy according to [1,6]. The EM/AS algorithm  for nominal attributes was used to reconstruct a probability distribution. The reconstruction for continuous attributes was performed according to the AS algorithm . , a reconstruction of a probability distribution was performed in every node divided into classes (for details about reconstruction types please refer to ).
If, and only if x ∈ [y, z] then the node A is in the subtree of the node B. The intervals for the exemplary trie are shown in square brackets in ﬁgure 1. Consequently, given a list of triples (node number,id,position) sorted by the node number and an interval associated with a node in the trie, one may easily ﬁnd all of the (id,position) pairs in the subtree of the node, by retrieving all of the triples for which the node number ﬁts within the interval. Such sorted list of triples may be easily implemented as a non unique B+ -Tree with node number being the key and (id,position) pair being the value.
Advances in Databases and Information Systems: 16th East European Conference, ADBIS 2012, Poznań, Poland, September 18-21, 2012. Proceedings by Leonardo Andrade Ribeiro, Theo Härder (auth.), Tadeusz Morzy, Theo Härder, Robert Wrembel (eds.)