| 书目名称 | Structure in Complex Networks | | 编辑 | J. Reichardt | | 视频video | | | 丛书名称 | Lecture Notes in Physics | | 图书封面 |  | | 描述 | .In the modern world of gigantic datasets, which scientists and practioners of all fields of learning are confronted with, the availability of robust, scalable and easy-to-use methods for pattern recognition and data mining are of paramount importance, so as to be able to cope with the avalanche of data in a meaningful way. This concise and pedagogical research monograph introduces the reader to two specific aspects - clustering techniques and dimensionality reduction - in the context of complex network analysis. The first chapter provides a short introduction into relevant graph theoretical notation; chapter 2 then reviews and compares a number of cluster definitions from different fields of science. In the subsequent chapters, a first-principles approach to graph clustering in complex networks is developed using methods from statistical physics and the reader will learn, that even today, this field significantly contributes to the understanding and resolution of the related statistical inference issues. Finally, an application chapter examines real-world networks from the economic realm to show how the network clustering process can be used to deal with large, sparse datasets whe | | 出版日期 | Book 2009 | | 关键词 | Clustering; Graph; Notation; Resolution; cognition; complex networks; data mining; learning; modeling; patter | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-540-87833-9 | | isbn_softcover | 978-3-642-09965-6 | | isbn_ebook | 978-3-540-87833-9Series ISSN 0075-8450 Series E-ISSN 1616-6361 | | issn_series | 0075-8450 | | copyright | Springer-Verlag Berlin Heidelberg 2009 |
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发表于 2025-3-21 16:14:10
