Mining Complex Networks
暫譯: 複雜網絡挖掘

Kamiński, Bogumil, Pralat, Pawel, Théberge, François

Mining Complex Networks
  • 出版商: CRC
  • 出版日期: 2026-05-15
  • 售價: $8,200
  • 貴賓價: 9.5 折 $7,790
  • 語言: 英文
  • 頁數: 312
  • 裝訂: Hardcover - also called cloth, retail trade, or trade
  • ISBN: 1041261918
  • ISBN-13: 9781041261919
  • 相關分類: Data-mining

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商品描述

This book concentrates on mining networks, a subfield within data science. Many data science problems can be viewed as a study of some properties of complex networks in which nodes represent the entities that are being investigated, and edges represent relations between these entities.

In these networks (for example, Instagram and Facebook online social networks), nodes not only contain some useful information (such as the user's profile, photos, tags) but are also internally connected to other nodes (relations based on follower requests, similar users' behavior, age, geographic location). Such networks are often large-scale, decentralized, and evolve dynamically over time.

Mining complex networks to understand the principles governing the organization and the behavior of such networks is crucial for a broad range of fields of study, including information and social sciences, economics, biology, and neuroscience.

The field has seen significant advancements since the first edition was published. Changes and updates to this edition include:

  • New material and examples on random geometric graphs
  • The chapter on node embeddings was augmented in several places including a discussion on classical vs. structural embeddings, more details on graph neural networks (GNNs), as well as other directions.
  • Several new tools and techniques are introduced on mining hypergraphs
  • New material on post-processing for overlapping communities
  • A new focus on a framework for embedding graphs codeveloped by the authors.
  • A short chapter on fairness in network mining models.

This book is aimed at being suitable for an upper-year undergraduate course or a graduate course.

商品描述(中文翻譯)

這本書專注於網絡挖掘，這是數據科學的一個子領域。許多數據科學問題可以被視為對複雜網絡某些屬性的研究，其中節點代表被調查的實體，而邊則代表這些實體之間的關係。

在這些網絡中（例如，Instagram 和 Facebook 的在線社交網絡），節點不僅包含一些有用的信息（如用戶的個人資料、照片、標籤），還與其他節點內部相連（基於關注請求、相似用戶行為、年齡、地理位置的關係）。這類網絡通常是大規模的、去中心化的，並且隨著時間的推移而動態演變。

挖掘複雜網絡以理解支配這些網絡組織和行為的原則，對於包括信息科學、社會科學、經濟學、生物學和神經科學等廣泛的研究領域至關重要。

自第一版出版以來，該領域已經取得了顯著的進展。本版的變更和更新包括：
- 新增隨機幾何圖的材料和範例
- 節點嵌入的章節在幾個地方進行了增補，包括對經典嵌入與結構嵌入的討論、圖神經網絡（GNNs）的更多細節，以及其他方向
- 引入了幾種新的工具和技術來挖掘超圖
- 新增有關重疊社區的後處理材料
- 新增一個由作者共同開發的圖嵌入框架的重點
- 一個關於網絡挖掘模型公平性的簡短章節

這本書旨在適合高年級本科課程或研究生課程。

作者簡介

Bogumil Kamiński is the Chairman of the Scientific Council for the Discipline of Economics and Finance at SGH Warsaw School of Economics. He is an expert in applications of mathematical modelling and artificial intelligence models to solve complex real-life problems. He is also a substantial opensource contributor to the development of the Julia language and its package ecosystem.

Pawel Pralat is a Professor of Mathematics at Toronto Metropolitan University, whose main research interests are in random graph theory, especially in modelling and mining complex networks. He has pursued collaborations with various industry partners as well as the Government of Canada. He has written more than 230 papers and 4 books with more than 170 collaborators.

François Théberge holds a BSc degree in applied mathematics from the University of Ottawa, an MSc in telecommunications from INRS, and a PhD in electrical engineering from McGill University. He has been employed by the Government of Canada since 1996 during which he was involved in the creation of the data science team as well as the research group now known as the Tutte Institute for Mathematics and Computing. He also holds an adjunct professorial position in the Department of Mathematics and Statistics at the University of Ottawa.

作者簡介(中文翻譯)

Bogumil Kamiński 是華沙經濟學院（SGH Warsaw School of Economics）經濟與金融學科科學委員會的主席。他是數學建模和人工智慧模型應用於解決複雜現實問題的專家。他也是 Julia 語言及其套件生態系統的重要開源貢獻者。

Pawel Pralat 是多倫多都市大學（Toronto Metropolitan University）的數學教授，他的主要研究興趣在於隨機圖理論，特別是在建模和挖掘複雜網絡方面。他與多個產業夥伴以及加拿大政府進行了合作。他已經撰寫了超過 230 篇論文和 4 本書，並與超過 170 位合作者合作。

François Théberge 擁有渥太華大學的應用數學學士學位、INRS 的電信碩士學位，以及麥吉爾大學的電機工程博士學位。自 1996 年以來，他一直在加拿大政府工作，期間參與了數據科學團隊的創建以及現在被稱為 Tutte 數學與計算研究所的研究小組。他還在渥太華大學數學與統計系擔任兼任教授。

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