| 書目名稱 | Frequent Pattern Mining | | 編輯 | Charu C. Aggarwal,Jiawei Han | | 視頻video | http://file.papertrans.cn/349/348246/348246.mp4 | | 概述 | Proposes numerous methods to solve some of the most fundamental problems in data mining and machine learning.Presents various simplified perspectives, providing a range of information to benefit both | | 圖書封面 |  | | 描述 | This comprehensive reference consists of 18 chapters from prominent researchers in the field. Each chapter is self-contained, and synthesizes one aspect of frequent pattern mining. An emphasis is placed on simplifying the content, so that students and practitioners can benefit from the book. Each chapter contains a survey describing key research on the topic, a case study and future directions. Key topics include: Pattern Growth Methods, Frequent Pattern Mining in Data Streams, Mining Graph Patterns, Big Data Frequent Pattern Mining, Algorithms for Data Clustering and more. Advanced-level students in computer science, researchers and practitioners from industry will find this book an invaluable reference. | | 出版日期 | Book 2014 | | 關(guān)鍵詞 | Association rules; Biometrics; Data classification; Data mining; Data stream pattern mining; Data streams | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-319-07821-2 | | isbn_softcover | 978-3-319-34689-2 | | isbn_ebook | 978-3-319-07821-2 | | copyright | Springer International Publishing Switzerland 2014 |
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