By Christophe Claramunt, Markus Schneider, Raymond Chi-Wing Wong, Li Xiong, Woong-Kee Loh, Cyrus Shahabi, Ki-Joune Li
This ebook constitutes the refereed complaints of the 14th foreign Symposium on Spatial and Temporal Databases, SSTD 2015, held in Hong Kong, China, in August 2015.
The 24 revised complete papers including eight demos awarded have been rigorously reviewed and chosen from sixty four submissions. The convention application has the scope on following topics: reachability question and course question, opposite question and indexing, navigation and routing, trajectory research, spatio-temporal methods, privateness and matching, similarity seek and development, key-phrase and pattern.
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Extra resources for Advances in Spatial and Temporal Databases: 14th International Symposium, SSTD 2015, Hong Kong, China, August 26-28, 2015. Proceedings
D3 <= n4 . dist ORDER BY n3 . obj ; RkNN COLD query, we will have to use an additional JOIN between the revcold and knnres DB tables. 6. We see that even the more complex RkNN query in COLD requires just a few lines of SQL code that will work on any recent PostgreSQL version without any need of third-party extensions or specialized index structures. In fact, all DB tables in COLD, use only standard B-tree primary key indexes, without any modiﬁcations. To satisfy this strict requirement, we eﬀectively compressed the index sizes by grouping rows per vertex (forcold table) or object (knnres table), or by hub and distance for knncold, objcold and rknncold.
HopDB answers only vertex-to-vertex queries and is a customized C++ solution that cannot be used with existing database systems and, hence, has limited practical applicability. This work presents a database framework that may service multiple distance queries on massive large-scale graphs. Our pure-SQL COLD framework (COmpressed Labels on the Database) can answer multiple exact distance queries (point-to-point, kNN) in addition to RkNN and one-to-many queries not handled by previous methods, rendering it a complete database solution for a variety of practical massive, large-scale graph problems.
In: 21st SIGSPATIAL International Conference on Advances in Geographic Information Systems, SIGSPATIAL 2013, Orlando, FL, USA, 5–8 November 2013, pp. 490–493 (2013) 18. : Better bounds for graph bisection. , Ferragina, P. ) ESA 2012. LNCS, vol. 7501, pp. 407–418. Springer, Heidelberg (2012) 19. : Optimizing landmark-based routing and preprocessing. In: CTS: 6th ACM SIGSPATIAL International Workshop on Computational Transportation Science, 5 November 2013, Orlando, FL, USA, p. 25 (2013) 20. : GRASP.