Mining Complex Networks

This book focuses on mining networks, a subfield of data science that uses scientific and computational tools to extract valuable knowledge from large data sets. It is suitable for an upper-year undergraduate course or a graduate course in programs such as data science, mathematics, computer science, business, engineering, physics, statistics, and social science. It also includes Jupiter notebooks that accompany the book and can be accessed on https://www.ryerson.ca/mining-complex-networks/.

Format: Hardback
Length: 264 pages
Publication date: 22 December 2021
Publisher: Taylor & Francis Ltd

This comprehensive textbook delves into the intricate realm of mining networks, a specialized branch within the vast field of data science. Data science employs a blend of scientific and computational techniques to extract valuable insights from vast data repositories. Once the data undergoes rigorous processing and cleansing, it undergoes comprehensive analysis and presentation to facilitate informed decision-making processes. The widespread adoption of data science and machine learning tools has permeated companies of all sizes. Networks, characterized by their vast scale, decentralized nature, and dynamic evolution over time, present unique challenges for exploration. Mining complex networks serves as a vital tool in understanding the underlying principles governing the organization and behavior of these intricate systems. Here are a few prominent applications of network mining:

Community Detection: This involves identifying groups of users with close friendships on social media platforms. It plays a crucial role in understanding social dynamics and user interactions.

Link Prediction: Predicting the likelihood of connections between users on social media platforms is another important application. This helps platforms optimize their recommendation systems and enhance user engagement.

Node Attribute Prediction: Analyzing the attributes of nodes in a network, such as user preferences or demographic information, can assist in personalized advertising and content recommendations.

Influential Node Detection: Identifying influential social media users who can effectively promote specific products or brands is a valuable aspect of marketing strategies.

This textbook is designed to cater to upper-year undergraduate students and graduate students enrolled in programs such as data science, mathematics, computer science, business, engineering, physics, statistics, and social science. Its comprehensive nature and rigorous approach make it an invaluable resource for enthusiasts and professionals seeking to expand their knowledge in the field of network mining.

To enhance the learning experience, the book is accompanied by Jupiter notebooks, available on the official website at https://www.ryerson.ca/mining-complex-networks/. These notebooks not only contain all the experiments presented in the textbook but also provide additional material and insights.

Bogumił Kamiński, the Chairman of the Scientific Council for Data Science at the Polish Academy of Sciences, has authored this textbook. His extensive expertise and contributions to the field of data science make him a respected authority in the field.

In conclusion, this textbook serves as a comprehensive guide to mining networks, offering a deep understanding of the principles, techniques, and applications of this specialized field. Whether you are a student, researcher, or professional seeking to advance your knowledge in data science, this textbook is an essential resource that will empower you to unlock the hidden treasures within complex networks.

Weight: 554g
Dimension: 160 x 242 x 22 (mm)
ISBN-13: 9781032112039