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Titlebook: New Frontiers in Applied Data Mining; PAKDD 2011 Internati Longbing Cao,Joshua Zhexue Huang,Jun Luo Conference proceedings 2012 Springer-Ve

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書(shū)目名稱New Frontiers in Applied Data Mining
副標(biāo)題PAKDD 2011 Internati
編輯Longbing Cao,Joshua Zhexue Huang,Jun Luo
視頻videohttp://file.papertrans.cn/666/665235/665235.mp4
概述State-of-the-art research.Fast-track conference proceedings.Unique visibility
叢書(shū)名稱Lecture Notes in Computer Science
圖書(shū)封面Titlebook: New Frontiers in Applied Data Mining; PAKDD 2011 Internati Longbing Cao,Joshua Zhexue Huang,Jun Luo Conference proceedings 2012 Springer-Ve
描述This book constitutes the thoroughly refereed post-conference proceedings of five international workshops held in conjunction with PAKDD 2011 in Shenzhen, China, in May 2011: the International Workshop on Behavior Informatics (BI 2011), the Workshop on Quality Issues, Measures of Interestingness and Evaluation of Data Mining Models (QIMIE 2011), the Workshop on Biologically Inspired Techniques for Data Mining (BDM 2011), the Workshop on Advances and Issues in Traditional Chinese Medicine Clinical Data Mining (AI-TCM 2011), and the Second Workshop on Data Mining for Healthcare Management (DMGHM 2011). The book also includes papers from the First PAKDD Doctoral Symposium on Data Mining (DSDM 2011). The?42 papers were carefully reviewed and selected from numerous submissions. The papers cover a wide range of topics discussing emerging techniques in the field of knowledge discovery in databases and their application domains extending to previously unexplored areas such as data mining based on optimization techniques from biological behavior of animals and applications in Traditional Chinese Medicine clinical research and health care management.
出版日期Conference proceedings 2012
關(guān)鍵詞cloud computing; genetic network programming; memetic algorithm; particle swarm optimization; recommende
版次1
doihttps://doi.org/10.1007/978-3-642-28320-8
isbn_softcover978-3-642-28319-2
isbn_ebook978-3-642-28320-8Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer-Verlag GmbH Berlin Heidelberg 2012
The information of publication is updating

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Longbing Cao,Joshua Zhexue Huang,Jun LuoState-of-the-art research.Fast-track conference proceedings.Unique visibility
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A Method of Similarity Measure and Visualization for Long Time Series Using Binary Patterns patterns. The matrix can be used to calculate the similarity and visualize the long time series. The experiments demonstrate that our approach not only can measure the long time series as well as the “bag of pattern” (BOP), but also can obtain better visual effects of the long time series visualiza
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