| 書目名稱 | Learning from Data Streams | | 副標題 | Processing Technique | | 編輯 | Jo?o Gama,Mohamed Medhat Gaber | | 視頻video | http://file.papertrans.cn/583/582932/582932.mp4 | | 概述 | Shows how to apply machine learning techniques to stream data processing.Details data stream mining approaches using clustering, predictive learning, and tensor analysis techniques.Presents applicatio | | 圖書封面 |  | | 描述 | .Sensor networks consist of distributed autonomous devices that cooperatively monitor an environment. Sensors are equipped with capacities to store information in memory, process this information and communicate with their neighbors. Processing data streams generated from wireless sensor networks has raised new research challenges over the last few years due to the huge numbers of data streams to be managed continuously and at a very high rate...The book provides the reader with a comprehensive overview of stream data processing, including famous prototype implementations like the Nile system and the TinyOS operating system. The set of chapters covers the state-of-art in data stream mining approaches using clustering, predictive learning, and tensor analysis techniques, and applying them to applications in security, the natural sciences, and education...This research monograph delivers to researchers and graduate students the state of the art in data stream processing in sensor networks. The huge bibliography offers an excellent starting point for further reading and future research. . | | 出版日期 | Book 2007 | | 關(guān)鍵詞 | LEGO Mindstorms; Mindstorms; Predictive Learning; Sensor Data; Sensor Networks; TinyOS; architectures; clus | | 版次 | 1 | | doi | https://doi.org/10.1007/3-540-73679-4 | | isbn_softcover | 978-3-642-09285-5 | | isbn_ebook | 978-3-540-73679-0 | | copyright | Springer-Verlag Berlin Heidelberg 2007 |
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