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Titlebook: Intelligence Science and Big Data Engineering. Big Data and Machine Learning Techniques; 5th International Co Xiaofei He,Xinbo Gao,Zhanchen

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书目名称Intelligence Science and Big Data Engineering. Big Data and Machine Learning Techniques
副标题5th International Co
编辑Xiaofei He,Xinbo Gao,Zhancheng Zhang
视频videohttp://file.papertrans.cn/470/469279/469279.mp4
丛书名称Lecture Notes in Computer Science
图书封面Titlebook: Intelligence Science and Big Data Engineering. Big Data and Machine Learning Techniques; 5th International Co Xiaofei He,Xinbo Gao,Zhanchen
描述The two-volume set LNCS 9242 + 9243 constitutes the proceedings of the 5th International Conference on Intelligence Science and Big Data Engineering, IScIDE 2015, held in Suzhou, China, in June 2015.  .The total of 126 papers presented in the proceedings was carefully reviewed and selected from 416 submissions. They deal with big data, neural networks, image processing, computer vision, pattern recognition and graphics, object detection, dimensionality reduction and manifold learning, unsupervised learning and clustering, anomaly detection, semi-supervised learning..
出版日期Conference proceedings 2015
关键词anomaly detection; big data; image representations; neural networks; unsupervised learning; cloud computi
版次1
doihttps://doi.org/10.1007/978-3-319-23862-3
isbn_softcover978-3-319-23861-6
isbn_ebook978-3-319-23862-3Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer International Publishing Switzerland 2015
The information of publication is updating

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Ranking Web Page with Path Trust Knowledge Graph, propose and construct Path Trust Knowledge Graph . model for assigning priority values to the unvisited web pages. For a given user specific topic ., its . contains five parts: (1) The context graph ., where . is the crawled history web page set and . includes the hyper link set among the history w
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Auroral Oval Boundary Modeling Based on Deep Learning Method,oleward boundary of the auroral oval are significant parameters of the auroral oval location. Thus auroral oval boundary modeling is an efficient way to study the location of auroral oval. As the location of the auroral oval boundary is subject to a variety of geomagnetic factors, there are some lim
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