By Kuan-Ching Li, Hai Jiang, Laurence T. Yang, Alfredo Cuzzocrea
"Data are generated at an exponential fee worldwide. via complex algorithms and analytics strategies, companies can harness this information, detect hidden styles, and use the findings to make significant judgements. Containing contributions from best specialists of their respective fields, this e-book bridges the distance among the vastness of huge info and the best computational tools for clinical and social discovery. It additionally explores comparable purposes in various sectors, masking applied sciences for media/data communique, elastic media/data garage, cross-network media/data fusion, SaaS, and more"-- �Read more...
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Extra info for Big data : algorithms, analytics, and applications
Mobile Intelligence (Wiley 2010) received an Honorable Mention by the American Publishers Awards for Professional and Scholarly Excellence (the PROSE Awards). He has won several best paper awards (including IEEE best and outstanding conference awards, such as the IEEE 20th International Conference on Advanced Information Networking and Applications [IEEE AINA-06]), one best paper nomination, the Distinguished Achievement Award (2005, 2011), and the Canada Foundation for Innovation Award (2003).
The Morgan Kaufmann Series in Computer Graphics and Geometric Modeling. Morgan Kaufmann, San Francisco, CA, 2006. B. Bustos, O. Pedreira and N. Brisaboa. A dynamic pivot selection technique for similarity search. In Proceedings of the First International Workshop on Similarity Search and Applications, pages 105–112, Washington, DC, 2008. IEEE Computer Society. 4. L. G. Ares, N. R. Brisaboa, M. F. Esteller, Ó. Pedreira and Á. S. Places. Optimal pivots to minimize the index size for metric access methods.
Similarity Search: The Metric Space Approach, volume 32 of Advances in Database Systems. Springer, Secaucus, NJ, 2006. 12. E. C. Gonzalez, K. Figueroa and G. Navarro. IEEE Transactions, on Pattern Analysis and Machine Intelligence, 30(9):1647–1658, 2008. 13. H. Mohamed and S. Marchand-Maillet. Quantized ranking for permutation-based indexing. In N. Brisaboa, O. Pedreira and P. Zezula, editors, Similarity Search and Applications, volume 8199 of Lecture Notes in Computer Science, pages 103–114.