By Tutut Herawan, Iwan Tri Riyadi Yanto, Mustafa Mat Deris (auth.), Ngoc Thanh Nguyen, Radosław Katarzyniak, Shyi-Ming Chen (eds.)
The e-book involves 32 prolonged chapters which were in keeping with chosen submissions to the poster consultation geared up in the course of the second Asian convention on clever info and Database platforms (24-26 March 2010 in Hue, Vietnam). The ebook is equipped into 4 elements dedicated to details retrieval and administration, carrier composition and user-centered technique, info mining and information extraction, and computational intelligence, respectively. All chapters within the booklet speak about theoretical and sensible concerns with regards to integration of synthetic intelligence and database applied sciences which will enhance new periods of clever details platforms. Such mixture of man-made intelligence and database applied sciences is a quick starting to be subfield of recent desktop technology, vital as a result of consistent improvement of networked details platforms. New worldwide multimedia platforms utilized by heterogeneous populations demand those advancements. The editors wish that the booklet may be necessary for graduate and PhD scholars of laptop technology, in addition to for mature teachers, researchers and practitioners attracted to powerful software of synthetic intelligence and database platforms to fashionable info environments. it's the wish of the editors that readers of this quantity can locate many inspiring rules and influential functional examples and use them of their destiny work.
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Additional info for Advances in intelligent information and database systems
Histogram, case 5 24 P. Lenkiewicz and K. Stencel can see, that the indexes are created properly. Some tables can be classified as belonging to this case because of the structure of the queries. Mainly these are complex queries containing subqueries, which are difficult for the query optimiser. Rewriting these queries or stored procedures can significantly improve performance. The other example is a query which contains functions in WHERE clause, what makes the existing indexes useless. Creating the functional index or index on computed column can help in this case.
Hence, P-R curves represent better the retrieval performance and allow comparing those of different systems. The closer the curve is to the right top corner, the better performance it represents. In order to have an average P-R curve of all queries, the P-R curve of each query is interpolated to the eleven standard recall levels 0%, 10%, …, 100% (). R . We also use average F-R curves at the eleven standard P+R recall levels to compare system performances. We conduct experiments to compare the results obtained by three different search models: 1.
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