Hanghang Tong's Books

Computational Approaches to the Network Science of Teams

By: Liangyue Li,Hanghang Tong

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Computational Approaches to the Network Science of Teams

By: Liangyue Li,Hanghang Tong

Surveys recent models and algorithms characterizing, predicting, optimizing, and explaining team performance in a variety of settings.

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Page Count

167

Publisher

Cambridge University Press

Published Date

ISBN 10

110849854X

ISBN 13

9781108498548

Network Connectivity

Concepts, Computation, and Optimization

By: Chen Chen,Hanghang Tong

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Network Connectivity

Concepts, Computation, and Optimization

By: Chen Chen,Hanghang Tong

Networks naturally appear in many high-impact domains, ranging from social network analysis to disease dissemination studies to infrastructure system design. Within network studies, network connectivity plays an important role in a myriad of applications. The diversity of application areas has spurred numerous connectivity measures, each designed for some specific tasks. Depending on the complexity of connectivity measures, the computational cost of calculating the connectivity score can vary significantly. Moreover, the complexity of the connectivity would predominantly affect the hardness of connectivity optimization, which is a fundamental problem for network connectivity studies. This book presents a thorough study in network connectivity, including its concepts, computation, and optimization. Specifically, a unified connectivity measure model will be introduced to unveil the commonality among existing connectivity measures. For the connectivity computation aspect, the authors introduce the connectivity tracking problems and present several effective connectivity inference frameworks under different network settings. Taking the connectivity optimization perspective, the book analyzes the problem theoretically and introduces an approximation framework to effectively optimize the network connectivity. Lastly, the book discusses the new research frontiers and directions to explore for network connectivity studies. This book is an accessible introduction to the study of connectivity in complex networks. It is essential reading for advanced undergraduates, Ph.D. students, as well as researchers and practitioners who are interested in graph mining, data mining, and machine learning.

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Page Count

151

Publisher

Springer Nature

Published Date

ISBN 10

3031037669

ISBN 13

9783031037665

Computational Approaches to the Network Science of Teams

By: Liangyue Li,Hanghang Tong

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Computational Approaches to the Network Science of Teams

By: Liangyue Li,Hanghang Tong

Business operations in large organizations today involve massive, interactive, and layered networks of teams and personnel collaborating across hierarchies and countries on complex tasks. To optimize productivity, businesses need to know: what communication patterns do high-performing teams have in common? Is it possible to predict a team's performance before it starts work on a project? How can productive team behavior be fostered? This comprehensive review for researchers and practitioners in data mining and social networks surveys recent progress in the emerging field of network science of teams. Focusing on the underlying social network structure, the authors present models and algorithms characterizing, predicting, optimizing, and explaining team performance, along with key applications, open challenges, and future trends.

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167

Publisher

Cambridge University Press

Published Date

ISBN 10

1108580238

ISBN 13

9781108580236

Data Mining

Concepts and Techniques

By: Jiawei Han,Jian Pei,Hanghang Tong

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Data Mining

Concepts and Techniques

By: Jiawei Han,Jian Pei,Hanghang Tong

Data Mining: Concepts and Techniques, Fourth Edition introduces concepts, principles, and methods for mining patterns, knowledge, and models from various kinds of data for diverse applications. Specifically, it delves into the processes for uncovering patterns and knowledge from massive collections of data, known as knowledge discovery from data, or KDD. It focuses on the feasibility, usefulness, effectiveness, and scalability of data mining techniques for large data sets. After an introduction to the concept of data mining, the authors explain the methods for preprocessing, characterizing, and warehousing data. They then partition the data mining methods into several major tasks, introducing concepts and methods for mining frequent patterns, associations, and correlations for large data sets; data classificcation and model construction; cluster analysis; and outlier detection. Concepts and methods for deep learning are systematically introduced as one chapter. Finally, the book covers the trends, applications, and research frontiers in data mining. - Presents a comprehensive new chapter on deep learning, including improving training of deep learning models, convolutional neural networks, recurrent neural networks, and graph neural networks - Addresses advanced topics in one dedicated chapter: data mining trends and research frontiers, including mining rich data types (text, spatiotemporal data, and graph/networks), data mining applications (such as sentiment analysis, truth discovery, and information propagattion), data mining methodologie and systems, and data mining and society - Provides a comprehensive, practical look at the concepts and techniques needed to get the most out of your data - Visit the author-hosted companion site, https://hanj.cs.illinois.edu/bk4/ for downloadable lecture slides and errata

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786

Publisher

Morgan Kaufmann

Published Date

ISBN 10

0128117613

ISBN 13

9780128117613

Mobile Data Mining

By: Yuan Yao,Xing Su,Hanghang Tong

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Mobile Data Mining

By: Yuan Yao,Xing Su,Hanghang Tong

This SpringerBrief presents a typical life-cycle of mobile data mining applications, including: data capturing and processing which determines what data to collect, how to collect these data, and how to reduce the noise in the data based on smartphone sensors feature engineering which extracts and selects features to serve as the input of algorithms based on the collected and processed data model and algorithm design In particular, this brief concentrates on the model and algorithm design aspect, and explains three challenging requirements of mobile data mining applications: energy-saving, personalization, and real-time Energy saving is a fundamental requirement of mobile applications, due to the limited battery capacity of smartphones. The authors explore the existing practices in the methodology level (e.g. by designing hierarchical models) for saving energy. Another fundamental requirement of mobile applications is personalization. Most of the existing methods tend to train generic models for all users, but the authors provide existing personalized treatments for mobile applications, as the behaviors may differ greatly from one user to another in many mobile applications. The third requirement is real-time. That is, the mobile application should return responses in a real-time manner, meanwhile balancing effectiveness and efficiency. This SpringerBrief targets data mining and machine learning researchers and practitioners working in these related fields. Advanced level students studying computer science and electrical engineering will also find this brief useful as a study guide.

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Springer

Published Date

ISBN 10

3030021017

ISBN 13

9783030021016

Data Mining

Concepts and Techniques

By: Jiawei Han,Jian Pei,Hanghang Tong

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Data Mining

Concepts and Techniques

By: Jiawei Han,Jian Pei,Hanghang Tong

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786

Publisher

Morgan Kaufmann

Published Date

ISBN 10

0128117613

ISBN 13

9780128117613

Network Connectivity

Concepts, Computation, and Optimization

By: Chen Chen,Hanghang Tong

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Network Connectivity

Concepts, Computation, and Optimization

By: Chen Chen,Hanghang Tong

Networks naturally appear in many high-impact domains, ranging from social network analysis to disease dissemination studies to infrastructure system design. Within network studies, network connectivity plays an important role in a myriad of applications. The diversity of application areas has spurred numerous connectivity measures, each designed for some specific tasks. Depending on the complexity of connectivity measures, the computational cost of calculating the connectivity score can vary significantly. Moreover, the complexity of the connectivity would predominantly affect the hardness of connectivity optimization, which is a fundamental problem for network connectivity studies. This book presents a thorough study in network connectivity, including its concepts, computation, and optimization. Specifically, a unified connectivity measure model will be introduced to unveil the commonality among existing connectivity measures. For the connectivity computation aspect, the authors introduce the connectivity tracking problems and present several effective connectivity inference frameworks under different network settings. Taking the connectivity optimization perspective, the book analyzes the problem theoretically and introduces an approximation framework to effectively optimize the network connectivity.Lastly, the book discusses the new research frontiers and directions to explore for network connectivity studies. This book is an accessible introduction to the study of connectivity in complex networks. It is essential reading for advanced undergraduates, Ph.D. students, as well as researchers and practitioners who are interested in graph mining, data mining, and machine learning.

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Page Count

165

Publisher

Morgan & Claypool Publishers

Published Date

ISBN 10

1636392962

ISBN 13

9781636392967

Mobile Data Mining

By: Yuan Yao,Xing Su,Hanghang Tong

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Mobile Data Mining

By: Yuan Yao,Xing Su,Hanghang Tong

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Springer

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ISBN 10

3030021017

ISBN 13

9783030021016

Book's by Hanghang Tong

Computational Approaches to the Network Science of Teams

Computational Approaches to the Network Science of Teams

Network Connectivity

Network Connectivity

Computational Approaches to the Network Science of Teams

Computational Approaches to the Network Science of Teams

Data Mining

Data Mining

Mobile Data Mining

Mobile Data Mining

Data Mining

Data Mining

Network Connectivity

Network Connectivity

Mobile Data Mining

Mobile Data Mining

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