Titlebook: Database Systems for Advanced Applications; 15th International C Hiroyuki Kitagawa,Yoshiharu Ishikawa,Chiemi Watana Conference proceedings

Ardent

0302-9743 volume contains contributions related to trajectories and moving objects, skyline queries, privacy and security, data streams, similarity search and event processing, storage and advanced topics, industrial, demo papers, and tutorials and panels.978-3-642-12025-1978-3-642-12026-8Series ISSN 0302-9743 Series E-ISSN 1611-3349

inconceivable

BOOR

Accessible

Distributed Cache Indexing for Efficient Subspace Skyline Computation in P2P Networksperty of ., we can optimize the utilization of the cached results for answering future skyline queries. Extensive evaluations on both synthetic and real dataset show that our approach can significantly reduce both bandwidth consumption and communication cost, and greatly shorten the response time.

老人病學(xué)

Efficiently Answering Probability Threshold-Based Shortest Path Queries over Uncertain Graphsntics that has been widely adopted for probabilistic data management, and develop efficient methods to find threshold-based SP path queries over an uncertain graph. Extensive experiments based on real data sets verified the effectiveness of the proposed methods.

向外才掩飾

Apraxia

PGP-mc: Towards a Multicore Parallel Approach for Mining Gradual Patternsarallelism in order to enhance the performances of the fastest existing one (GRITE). Through a detailed experimental study, we show that our parallel algorithm scales very well with the number of cores available.

富饒

Effectively Inferring the Search-for Node Type in XML Keyword Searcha for inferring the search-for node type suffers from . and . problems..In this paper, we propose a . scheme as well as a novel algorithm . to resolve these two problems. Experimental results are provided to verify the effectiveness of our approach.

閑聊

Inorganic and Organometallic Compoundses in a dataset vary widely. In this paper, we exploit the notion of “item-to-pattern difference” and propose multiple . based FP-growth-like approach to efficiently discover rare association rules. Experimental results show that the proposed approach is efficient.

剝削

https://doi.org/10.1007/978-3-030-41552-5ming in a high speed, the solution should be capable of handling a large amount of evolutions in short time and returning the top-. results as soon as possible. The experimental results on real data sets show that our proposed solution is very efficient and effective.