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In many small dataset learning tasks, however, owing to the incomplete data structure, the explicit information for decision making is limited. This research aims to learn more information hidden inside the incomplete data by adding more samples to strengthen data structures. Based on the prior knowledge provided by the M5' model tree, the proposed research mechanism generates artificial samples to...
Related data streams refer to data streams that can be joined together by matching their join attributes. Existing research on learning from related data streams is based on an assumption that all streams arrive at a central processing unit in a synchronous way, such that in an arbitrary sliding window, all tuples of the streams can be perfectly joined together. This assumption, however, does not...
On large scale dataset, the effect of automatic text classification is now still far from perfect. It's a common agreement that more sufficient text semantic meaning be adopted in text representation to deal with the challenge. This paper introduces semantic meaning of coreference in and to improve traditional BOW representation. The result of text classification experiment shows that, contrasted...
In many applications including network monitoring, Web click stream analysis, sensor networks, detection of network intrusions, telecommunications data management and financial applications, data arrives in a stream fashion. The main focus in algorithms for data streams has been on efficient construction of synopsis data structures. This paper introduces the problem of construction of synopsis data...
As modeling and visualization applications proliferate, there arises a need to reduce three dimensional unorganized data points in reverse engineering. To meet the demand for both geometric and engineering fidelity of the reduction, a fuzzy-clustering-based reduction method is presented. As an effective extension to the existing pure geometric reduction methods, a hybrid heuristic is introduced. It...
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