Download Advanced Database Query Systems: Techniques, Applications by Li Yan, Zongmin Ma PDF

By Li Yan, Zongmin Ma

Databases are designed to help info garage, processing, and retrieval actions with regards to info administration. using databases in quite a few purposes has ended in an important wealth of information, which populates many varieties of databases round the world.Advanced Database question platforms: suggestions, purposes and applied sciences makes a speciality of applied sciences and methodologies of database queries, XML and metadata queries, and functions of database question platforms, aiming at offering a unmarried account of applied sciences and practices in complex database question platforms. This e-book offers the cutting-edge info for lecturers, researchers and practitioners who're drawn to the examine, use, layout and improvement of complex and rising database queries with final objective of establishing abilities for exploiting the possibilities of the information and data society.

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Probabilistic ranking of database query results. Proceedings of the 30th International Conference on Very Large Data Base, (pp. 888–899). Chen, Z. , & Li, T. (2007). Addressing diverse user preferences in SQL-Query-Result navigation. Proceedings of the ACM SIGMOD International Conference on Management of Data, (pp. 641-652). , & Young, N. (2005). The reverse greedy algorithm for the metric k-median problem. Information Processing Letters, 97, 68–72. , & Sudarshan, S. (2006). Ordering the attributes of query results.

5-Categorization algorithm does not. Moreover, our algorithm can use a few clusters to representative a large scale tuples without lose accuracy (it will be tested in the next experiment). The results show that using our approach, on average a subject only needs to visit no more than 8 tuples or intermediate nodes for queries Q1, Q2, Q3, and Q4 to find the first relevant tuple, and needs to visit about 18 tuples or intermediate nodes for Q5. The total navigational cost for our algorithm is less than 45 for the former four queries, and is less than 80 for Q5.

Algorithm Solution Based on the solutions mentioned above, we can now describe how we construct a category tree. Since the problem of finding a tree with minimal category cost is NP-hard, we propose an approximate algorithm (see Algorithm 6). After building the category tree, the user can go along with the branches of tree to find the interesting answers. , showing tuples (option ‘ShowTuples’) and showing category (option ‘ShowCat’). When the user chosen the option ‘ShowTuples’ on a node (an intermediate node or a leaf node), the system will provide the items satisfying all conditions from the root to the current node.

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