Download e-book for kindle: Advanced Database Query Systems: Techniques, Applications by Li Yan, Zongmin Ma

By Li Yan, Zongmin Ma

ISBN-10: 160960475X

ISBN-13: 9781609604752

ISBN-10: 1609604768

ISBN-13: 9781609604769

Databases are designed to help facts garage, processing, and retrieval actions with regards to info administration. using databases in a variety of functions has ended in a major wealth of knowledge, which populates many varieties of databases round the world.Advanced Database question structures: innovations, purposes and applied sciences specializes in applied sciences and methodologies of database queries, XML and metadata queries, and purposes of database question platforms, aiming at delivering a unmarried account of applied sciences and practices in complicated database question structures. This booklet offers the state-of-the-art info for teachers, researchers and practitioners who're attracted to the examine, use, layout and improvement of complex and rising database queries with final goal of creating potential for exploiting the possibilities of the information and information society.

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Evaluating top-k queries over Web-accessible databases. Proceedings of the 18th International Conference on Data Engineering, (pp. 369-380). , & Shneiderman, B. (1999). Readings in information visualization: using vision to think. Morgan Kaufmann. , & Hwang, S. (2004). Automatic categorization of query results. Proceedings of the ACM SIGMOD International Conference on Management of Data, (pp. 755–766). , & Weikum, G. (2004). Probabilistic ranking of database query results. Proceedings of the 30th International Conference on Very Large Data Base, (pp.

2002). Optimizing search engines using clickthrough data. Proceedings of the ACM Conference on Knowledge Discovery and Data Mining, (pp. 133–142). 25 Automatic Categorization of Web Database Query Results Kießling, W. (2002). Foundations of preferences in database systems. Proceedings of the 28th International Conference on Very Large Data Bases, (pp. 311-322). , & Sahami, M. (1997). Hierarchically classifying documents using very few words. Proceedings of the 14th International Conference on Machine Learning, (pp.

We then group tuples according to their Si, and each group forms a cluster. Each cluster is assigned a class label. The probability of users being interested in cluster Ci is computed as the sum of probabilities that a user asks a query in Si. This equals the sum of frequencies of queries in Si divided by the sum of frequencies of all queries in the pruned query history H. Example 2. Suppose that there are four queries Q1, Q2, Q3, and Q4 and 15 tuples r1, r2, …, r15. Q1 returns first 10 tuples r1, r2, …, r10, Q2 returns the first 9 tuples r1, r2, …, r9, and r14, Q3 returns r11, r12 and r14, and Q4 returns r15.

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

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