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Titlebook: Data Mining for Service; Katsutoshi Yada Book 2014 Springer-Verlag Berlin Heidelberg 2014 Data Mining.Domain Knowledge.Large Database.Sens

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樓主: 生長變吼叫
41#
發(fā)表于 2025-3-28 16:55:31 | 只看該作者
Panel Data Analysis Via Variable Selection and Subject Clusteringble of interest. A regression on many irrelevant regressors will lead to wrong predictions. To address these two issues, we propose a novel approach, called ., which derives underlying linear models by first selecting variables highly correlated to the variable of interest and then clustering subjec
42#
發(fā)表于 2025-3-28 19:11:59 | 只看該作者
43#
發(fā)表于 2025-3-29 02:38:01 | 只看該作者
Text Mining of Business-Oriented Conversations at a Call Centerngthy and redundant. In this research, we define the model of the business-oriented conversations and propose a mining method to identify segments that make impact on the outcome of the conversation and extract useful expressions in each identified segments. In the experiment, we process the real da
44#
發(fā)表于 2025-3-29 03:38:01 | 只看該作者
A Matrix Factorization Framework for Jointly Analyzing Multiple Nonnegative Data Sourcesrieval performance exceeds the existing state-of-the-art techniques. The proposed solution provides a generic framework and can be applicable to a wider context in data mining wherever one needs to exploit mutual and individual knowledge present across multiple data sources.
45#
發(fā)表于 2025-3-29 10:50:53 | 只看該作者
46#
發(fā)表于 2025-3-29 14:04:24 | 只看該作者
Text Document Cluster Analysis Through Visualization of 3D Projectionsant to generate a display (or users may choose any three orthogonal axes). We conducted implementation studies to demonstrate the value of our system with an artificial data set and a de facto benchmark news article dataset from the United States NIST Text REtrieval Competitions (TREC).
47#
發(fā)表于 2025-3-29 17:09:12 | 只看該作者
48#
發(fā)表于 2025-3-29 22:35:33 | 只看該作者
49#
發(fā)表于 2025-3-30 00:40:13 | 只看該作者
https://doi.org/10.1007/978-3-642-51833-1with terms such as activation, interferon, cell and signaling. Further examination of several clusters, using gene pathway databases as well as natural language processing tools, revealed that nonnegative tensor factorization accurately identified genes and TFs in well established signaling pathways
50#
發(fā)表于 2025-3-30 07:13:26 | 只看該作者
https://doi.org/10.1007/978-3-642-51833-1ngthy and redundant. In this research, we define the model of the business-oriented conversations and propose a mining method to identify segments that make impact on the outcome of the conversation and extract useful expressions in each identified segments. In the experiment, we process the real da
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