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Big data analysis is a main challenge we meet recently. Cloud computing is attracting more and more big data analysis applications, due to its well scalability and fault-tolerance. Some aggregation functions, like SUM, can be computed in parallel, because they satisfy distributive law of addition. Unfortunately, some of statistical functions are not naturally parallelizable. That means they do not...
In this paper, we analyse the data access characteristics of a typical XML information retrieval system and propose a new query aware buffer replacement algorithm based on prediction of Minimum Reuse Distance (MRD for short). The algorithm predicts an object's next reference distance according to the retrieval system's running status and replaces the objects that have maximum reuse distances. The...
Connected component labeling is an indispensable and one of most time consuming tasks of the applications in computer vision. Many labeling algorithms have been introduced, such as scan plus connection table, scan plus union-find, and contour tracing etc. They would rather use byte data than bit data to represent the binary pixel, which is either 1 or 0, due to the heavy cost of bitwise operations...
Based on the statistical learning theory support vector machine focuses on the machine learning strategies under small samples and gets better generalization ability than those tools based on the experience risk minimization principle. Its classing or regression performance will be affected by relative super-parameters. An improved multi object optimization algorithm based on simulated annealing is...
With the rapid development of information retrieval technology and daily increasing information in the Internet, common users can retrieve many text-based database and get part of the information through the search engines such as Google, and Baidu. However, there is a great amount of data contained in the background relational database of web pages. So there are many researches focusing on the search...
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