| 书目名称 | Link Mining: Models, Algorithms, and Applications | | 编辑 | Philip S. Yu,Jiawei Han,Christos Faloutsos | | 视频video | | | 概述 | Link mining has become an emerging field of data mining, which has a high impact in various important applications such as text mining, social network analysis, collaborative filtering, and bioinforma | | 图书封面 |  | | 描述 | With the recent flourishing research activities on Web search and mining, social network analysis, information network analysis, information retrieval, link analysis, and structural data mining, research on link mining has been rapidly growing, forming a new field of data mining. Traditional data mining focuses on "flat" or “isolated” data in which each data object is represented as an independent attribute vector. However, many real-world data sets are inter-connected, much richer in structure, involving objects of heterogeneous types and complex links.Hence, the study of link mining will have a high impact in various important applications such as Web and text mining, social network analysis, collaborative filtering, and bioinformatics.Link Mining: Models, Algorithms and Applications focuses on the theory and techniques as well as the related applications for link mining, especially from an interdisciplinary point of view.Due to the high popularity of linkage data, extensive applications ranging from governmental organizations to commercial businesses to people‘s daily life call for exploring the techniques of mining linkage data.This book provides a comprehensive coverage of the | | 出版日期 | Book 2010 | | 关键词 | Clustering; algorithms; bioinformatics; classification; collaborative filtering; data cleansing; data mini | | 版次 | 1 | | doi | https://doi.org/10.1007/978-1-4419-6515-8 | | isbn_softcover | 978-1-4939-0147-0 | | isbn_ebook | 978-1-4419-6515-8 | | copyright | Springer Science+Business Media, LLC 2010 |
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发表于 2025-3-21 19:57:13
