By Sourav S. Bhowmick, Curtis Dyreson, Christian S. Jensen, Mong Li Lee, Agus Muliantara, Bernhard Thalheim

These volumes set LNCS 8421 and LNCS 8422 constitutes the refereed lawsuits of the nineteenth overseas convention on Database platforms for complex purposes, DASFAA 2014, held in Bali, Indonesia, in April 2014. The sixty two revised complete papers awarded including 1 prolonged summary paper, four commercial papers, 6 demo displays, three tutorials and 1 panel paper have been conscientiously reviewed and chosen from a complete of 257 submissions. The papers disguise the next issues: enormous information administration, indexing and question processing, graph info administration, spatio-temporal facts administration, database for rising undefined, info mining, probabilistic and unsure information administration, internet and social facts administration, defense, privateness and belief, key-phrase seek, facts move administration and information quality.

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Extra info for Database Systems for Advanced Applications: 19th International Conference, DASFAA 2014, Bali, Indonesia, April 21-24, 2014. Proceedings, Part II

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C1,TF1,TE1,U1,A1 C1,TF2,TE2,U2,A2 C2,TF3,TE3,U3,A3 ... C3,TF4,TE4,U1,A4 C3,TF5,TE5,U4,A5 C4,TF6,TE6,U1,A6 ... C1 < C2 < C3 < C4 TF1 =TF3< TF2 is a STP about Pi captured by a surveillance camera at the location Locij and at the time Tij n - The length of ζi .

28 10 C. Sha et al. Table 3. 2 the first situation, we use only one ”sonar” data set. From Table 2, it can be seen that the running time of Eigcons grows more fast with more classifiers. While the others except SubmEP ent have a slower growth trend and the running time is much less than Eigcons method. For SubmEP ent, the running time is worse than others. The reason is that the estimation of Ent(HS ) is time consuming. In searching procedure, we calculate entropy of different subsets k ∗ l time, while we only need to calculate pairwise sim(hi , hj ) once.

One prominent research task is automatic image tagging. By means of bridging semantic gap [19] between visual representations and people’s interpretations of the same image, well labelled images benefit a lot of multimedia applications, such as image retrieval, indexing and visual event detection. However, among around 100 billion images existing on the Internet, only a very limited percentage of them are annotated [20]. Consequently, developing an efficient and effective automatic image tagging model is in high demand.

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