By Li Yan, Zongmin Ma

ISBN-10: 160960475X

ISBN-13: 9781609604752

ISBN-10: 1609604768

ISBN-13: 9781609604769

Databases are designed to aid info garage, processing, and retrieval actions concerning facts administration. using databases in a number of purposes has ended in an incredible wealth of information, which populates many varieties of databases round the world.Advanced Database question platforms: innovations, functions and applied sciences makes a speciality of applied sciences and methodologies of database queries, XML and metadata queries, and purposes of database question platforms, aiming at supplying a unmarried account of applied sciences and practices in complicated database question platforms. This e-book offers the state-of-the-art info for lecturers, researchers and practitioners who're drawn to the examine, use, layout and improvement of complicated and rising database queries with final goal of creating capabilities for exploiting the possibilities of the knowledge and information society.

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Extra resources for Advanced Database Query Systems: Techniques, Applications and Technologies

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The queries q2, q4, q6 and q15 produce alternative answers to the original query q: (q2) all employees under 30 who earn at least 40K€; (q4) all female employees under 32 who earn at least 40K€; (q6) all female employees under 31 who earn at least 39K€; and (q15) all female employees under 30 who earn at least 37K€. These answers can be delivered by SEAVE to the user as ‘the best it could do’ to satisfy the query q. , various combinations of the values of attributes) to identify MGSs/XGFs. CoBase The CoBaseiii (Chu, Yang, Chiang, Minock, Chow & Larson, 1996) system augments the database with Type Abstraction Hierarchies (TAHs) to control the query generalization process.

We experiment with datasets generated for the following parameters: n = 300, m = 600, l = {4, 8, 16, 32}, noise = {2, 4, 8,…, 128} for swaps. Figure 6 shows the performance of the algorithms as a function of the amount of noise. The y axis is the ratio: F(A)/F(INP), for A = {Greedy, Greedy-Refine}, where the Greedy- Refine algorithm is proposed in this chapter (Algorithm 3), while the Greedy algorithm is proposed in [2]. We compare them here since they all aim at solving the same problem (clustering problem).

The task of the algorithms is to rediscover the clustering model used for the data generation. Given a cluster center, each query from the same cluster is generated by adding to the center a specified amount of noise of a specific type. We consider two types of noise: swaps and shifts. The swap means that ‘0’ and ‘1’ elements from the initial order are picked and their positions in the order are exchanged. For the shifts we pick a random element and we move it to a new position, either earlier (or later) in the order.

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Advanced Database Query Systems: Techniques, Applications and Technologies by Li Yan, Zongmin Ma

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