Download Database Systems for Advanced Applications: 15th by Nan Chen, Lidan Shou, Gang Chen, Ke Chen, Yunjun Gao PDF

By Nan Chen, Lidan Shou, Gang Chen, Ke Chen, Yunjun Gao (auth.), Hiroyuki Kitagawa, Yoshiharu Ishikawa, Qing Li, Chiemi Watanabe (eds.)

This quantity set LNCS 5981 and LNCS 5982 constitutes the refereed lawsuits of the fifteenth overseas convention on Database structures for complicated functions, DASFAA 2010, held in Tsukuba, Japan, in April 2010. The 39 revised complete papers and sixteen revised brief papers provided including three invited keynote papers, 22 demonstration papers, 6 business papers, and a couple of keynote talks have been rigorously reviewed and chosen from 285 submissions. The papers of the 1st quantity are equipped in topical sections on P2P-based applied sciences, information mining applied sciences, XML seek and matching, graphs, spatial databases, XML applied sciences, time sequence and streams, complicated facts mining, question processing, internet, sensor networks and communications, info administration, in addition to groups and internet graphs. the second one quantity comprises contributions concerning trajectories and relocating items, skyline queries, privateness and protection, info streams, similarity seek and occasion processing, garage and complex issues, business, demo papers, and tutorials and panels.

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Additional info for Database Systems for Advanced Applications: 15th International Conference, DASFAA 2010, Tsukuba, Japan, April 1-4, 2010, Proceedings, Part II

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The basic idea is to employ a clustering-based anonymization algorithm to group similar trajectories and minimize the data distortion caused by anonymization through a careful selection of representative trajectories. We propose a C-Tree (ClusterTree) to speed up the clustering process and develop methods to incrementally calculating error rates. The rest of the paper is organized as follows: Section 2 reviews related work, Section 3 presents our proposed approach, Section 4 reports experimental results, and Section 5 concludes the paper with lessons learned and future research directions.

If more than one clusters found then 12. find the cluster with the smallest error rate 13. if error rate after adding T rj does not exceed threshold then 14. return the cluster found Fig. 5. Algorithm of Finding Clusters Privacy-Preserving Location Publishing under Road-Network Constraints 25 Road ID Original Anonymized + C1 r1+ r3− r10− ... r1 30 33 − 15 50 53 + 35 15 51 57 35 80 85 ... ... ... ... − + r2 r3 ... Cx r6− r7− r15− ... rn − ... + − Fig. 6. Anonymization Table it yields the smallest error rate after inserting T rj; (ii) its new error rate is below the global threshold Err.

We can also see that the cost of queries increases with the date cardinality for all the three kinds of indexes. However, for the B x -tree and the B s -tree, the update cost is not apparently affected by the dataset size. In addition, for all the three kinds of indexes, the update cost is much lower than the query cost. In the rest experiments, the default dataset size is 100K. Figure 5 (e) and ( f ) shows the average number of I/Os and CPU time per KNN query while varying K from 5 to 50. Observe that the effect of k is not very significant.

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