Download Advances in Spatial and Temporal Databases: 11th by Mor Naaman (auth.), Nikos Mamoulis, Thomas Seidl, Torben PDF

By Mor Naaman (auth.), Nikos Mamoulis, Thomas Seidl, Torben Bach Pedersen, Kristian Torp, Ira Assent (eds.)

This quantity constitutes the refereed complaints of the eleventh foreign Symposium on Spatial and Temporal Databases, SSTD 2009, held in Aalborg, Denmark, in July 2009.

The 20 revised complete papers provided including three keynotes, 7 brief papers, and 10 demonstration papers, have been completely reviewed and chosen from a complete of sixty two examine submissions and eleven demonstration submissions. The papers are equipped in topical sections on spatial and movement networks, integrity and defense, doubtful facts and new applied sciences, indexing and tracking relocating gadgets, complicated queries, in addition to on types and languages.

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Extra info for Advances in Spatial and Temporal Databases: 11th International Symposium, SSTD 2009 Aalborg, Denmark, July 8-10, 2009 Proceedings

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Below, we first classify the location updates and explain each of the classes in isolation; thereafter, we discuss how ER-CkNN implements all cases simultaneously. 1 Data and Query Object Location Updates With ER-CkNN, we classify each object location update into following three categories based on the type of the movement: resident updates, inbound updates, and outbound updates. The resident updates are those which indicate an object has been resident among the active-edges of the query since last update, either staying still or moving from one active-edge to another.

Below, we first classify the location updates and explain each of the classes in isolation; thereafter, we discuss how ER-CkNN implements all cases simultaneously. 1 Data and Query Object Location Updates With ER-CkNN, we classify each object location update into following three categories based on the type of the movement: resident updates, inbound updates, and outbound updates. The resident updates are those which indicate an object has been resident among the active-edges of the query since last update, either staying still or moving from one active-edge to another.

Consider a query point q looking for data object p which was previously found by q . If an on-line shortest path computation, from q to p, reaches q during the scan, then there is no need to continue the computation as ER-CkNN already knows the shortest path from q to p. 34 U. Demiryurek, F. Banaei-Kashani, and C. Shahabi (a) First Step (b) Final ER Fig. 4. Using ER (Euclidean Restriction) with ER-CkNN Algorithm 1. 2 Refine Step Once at the refine step, we have m > k. We denote the set of m − k objects that were added to the candidate set as P (in Figure 4(a), P = {p3 , p4 }).

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