Mining Complex Networks.

This book concentrates on mining networks, a subfield within data science. Data science uses scientific and computational tools to extract valuable knowledge from large data sets. Once data is processed and cleaned, it is analyzed and presented to support decision making processes. Data science and...

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Bibliographic Details
Main Author: Kamiński, Bogumił
Corporate Author: Taylor & Francis
Other Authors: Prałat, Paweł, Théberge, François
Format: eBook
Language:English
Published: [Place of publication not identified] : Chapman and Hall/CRC, 2021.
Edition:First edition.
Subjects:
Online Access:Connect to the full text of this electronic book
Description
Summary:This book concentrates on mining networks, a subfield within data science. Data science uses scientific and computational tools to extract valuable knowledge from large data sets. Once data is processed and cleaned, it is analyzed and presented to support decision making processes. Data science and machine learning tools have become widely used in companies of all sizes. Networks are often large-scale, decentralized, and evolve dynamically over time. Mining complex networks to understand the principles governing the organization and the behaviour of such networks is crucial for a broad range of fields of study. Here are a few selected typical applications of mining networks: Community detection (which users on some social media platform are close friends), Link prediction (who is likely to connect to whom on such platforms), Node attribute prediction (what advertisement should be shown to a given user of a particular platform to match their interests), Influential node detection (which social media users would be the best ambassadors of a specific product). This textbook 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. This book can be successfully used by all enthusiasts of data science at various levels of sophistication to expand their knowledge or consider changing their career path. Jupiter notebooks (in Python and Julia) accompany the book and can be accessed on https://www.ryerson.ca/mining-complex-networks/. These not only contain all of the experiments presented in the book yet also include additional material.
Physical Description:1 online resource (xiv, 264 pages).
ISBN:9781003218869
1003218865
9781000515909
1000515907
9781000515855
1000515850