Download Advanced Database Query Systems: Techniques, Applications by Li Yan, Zongmin Ma PDF
By Li Yan, Zongmin Ma
Databases are designed to aid information garage, processing, and retrieval actions on the topic of info administration. using databases in a number of purposes has led to an incredible wealth of knowledge, which populates many sorts of databases round the world.Advanced Database question platforms: strategies, purposes and applied sciences specializes in applied sciences and methodologies of database queries, XML and metadata queries, and functions of database question structures, aiming at supplying a unmarried account of applied sciences and practices in complex database question platforms. This e-book offers the state-of-the-art details for teachers, researchers and practitioners who're drawn to the learn, use, layout and improvement of complex and rising database queries with final target of creating advantage for exploiting the possibilities of the knowledge and information society.
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2271622. 251855, where, we choose the value ‘987’ as the partition value. 5 algorithm. However, the main difference between our algorithm and the existing decision tree construction algorithm is how to compute the gain of a partition. Our approach wants to reduce the category cost of visiting intermediate nodes (includes the tuples in them if user choose to explore them) and the cost of visiting tuples in the leaves. Our following analysis will show that information gain ignores the cost of visiting tupes, and the existing category tree construction algorithm proposed by Chakrabarti et.
Al. (Chen & Li, 2007). According to the definition in (Chen & Li, 2007), the perfect tree is that their leaves only contain tuples of on class and can not be partitioned further. In fact, the perfect tree is a decision tree. Given a perfect tree T with N tuples and k classes, where each class Ci in T has Ni tuples. The enk tropy E(T) = − ∑ i =1 Ni N log i approximates the average length of root-to-leaf paths for all tuples in T. N N Since T is a perfect tree, its leaves contain only one class per node.
We did observe that users started with a general query which returned many answers, and then gradually refined the query until it returned a small number of answers. Algorithm: We implemented all algorithms in C# and connected to the RDBMS through ADO. The clusters are stored by adding a column to the data table to store the class labels of each tuple. 002. We have developed an interface that allows users to classify query results using generated trees. Comparison: We compare our create tree algorithm (henceforth referred to as Cost-based algorithm) with the algorithm proposed by Chakrabarti et.