| 書目名稱 | On Uncertain Graphs | | 編輯 | Arijit Khan,Yuan Ye,Lei Chen | | 視頻video | http://file.papertrans.cn/702/701100/701100.mp4 | | 叢書名稱 | Synthesis Lectures on Data Management | | 圖書封面 |  | | 描述 | Large-scale, highly interconnected networks, which are often modeled as graphs, pervade both our society and the natural world around us. Uncertainty, on the other hand, is inherent in the underlying data due to a variety of reasons, such as noisy measurements, lack of precise information needs, inference and prediction models, or explicit manipulation, e.g., for privacy purposes. Therefore, uncertain, or probabilistic, graphs are increasingly used to represent noisy linked data in many emerging application scenarios, and they have recently become a hot topic in the database and data mining communities. Many classical algorithms such as reachability and shortest path queries become #P-complete and, thus, more expensive over uncertain graphs. Moreover, various complex queries and analytics are also emerging over uncertain networks, such as pattern matching, information diffusion, and influence maximization queries. In this book, we discuss the sources of uncertain graphs and their applications, uncertainty modeling, as well as the complexities and algorithmic advances on uncertain graphs processing in the context of both classical and emerging graph queries and analytics. We emphasi | | 出版日期 | Book 2018 | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-031-01860-2 | | isbn_softcover | 978-3-031-00732-3 | | isbn_ebook | 978-3-031-01860-2Series ISSN 2153-5418 Series E-ISSN 2153-5426 | | issn_series | 2153-5418 | | copyright | Springer Nature Switzerland AG 2018 |
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