Visual Analysis of Multilayer Networks, McGee, Fintan Renoust, Benjamin Archambault, Daniel Ghoniem, Mohammad Kerren, Andreas Pinaud, Bruno

Автор: Akutsu Tatsuya
Название: Algorithms for Analysis, Inference, and Control of Boolean Networks
ISBN: 9813233427 ISBN-13(EAN): 9789813233423
Издательство: World Scientific Publishing
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Цена: 95040.00 T
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Описание:

The Boolean network (BN) is a mathematical model of genetic networks and other biological networks. Although extensive studies have been done on BNs from a viewpoint of complex systems, not so many studies have been undertaken from a computational viewpoint. This book presents rigorous algorithmic results on important computational problems on BNs, which include inference of a BN, detection of singleton and periodic attractors in a BN, and control of a BN. This book also presents algorithmic results on fundamental computational problems on probabilistic Boolean networks and a Boolean model of metabolic networks. Although most contents of the book are based on the work by the author and collaborators, other important computational results and techniques are also reviewed or explained.

Автор: McGee Fintan, Renoust Benjamin, Archambault Daniel
Название: Visual Analysis of Multilayer Networks
ISBN: 1636391451 ISBN-13(EAN): 9781636391458
Издательство: Mare Nostrum (Eurospan)
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Цена: 89630.00 T
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Описание: The emergence of multilayer networks as a concept from the field of complex systems provides many new opportunities for the visualization of network complexity, and has also raised many new exciting challenges. The multilayer network model recognizes that the complexity of relationships between entities in real-world systems is better embraced as several interdependent subsystems (or layers) rather than a simple graph approach. Despite only recently being formalized and defined, this model can be applied to problems in the domains of life sciences, sociology, digital humanities, and more. Within the domain of network visualization there already are many existing systems, which visualize data sets having many characteristics of multilayer networks, and many techniques, which are applicable to their visualization. In this Synthesis Lecture, we provide an overview and structured analysis of contemporary multilayer network visualization. This is not only for researchers in visualization, but also for those who aim to visualize multilayer networks in the domain of complex systems, as well as those solving problems within application domains. We have explored the visualization literature to survey visualization techniques suitable for multilayer network visualization, as well as tools, tasks, and analytic techniques from within application domains. We also identify the research opportunities and examine outstanding challenges for multilayer network visualization along with potential solutions and future research directions for addressing them.

Автор: De Domenico
Название: Multilayer Networks: Analysis and Visualization
ISBN: 303075717X ISBN-13(EAN): 9783030757175
Издательство: Springer
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Цена: 139750.00 T
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Описание: The adoption of multilayer analysis techniques is rapidly expanding across all areas of knowledge, from social sciences (the first facing the complexity of such structures, decades ago) to computer science, from biology to engineering. However, until now, no book has dealt exclusively with the analysis and visualization of multilayer networks. Multilayer Networks: Analysis and Visualization provides a guided introduction to one of the most complete computational frameworks, named muxViz, with introductory information about the underlying theoretical aspects and a focus on the analytical side. Dozens of analytical scripts and examples to use the muxViz library in practice, by means of the Graphical User Interface or by means of the R scripting language, are provided. In addition to researchers in the field of network science, as well as practitioners interested in network visualization and analysis, this book will appeal to researchers without strong technical or computer science background who want to learn how to use muxViz software, such as researchers from humanities, social science and biology: audiences which are targeted by case studies included in the book. Other interdisciplinary audiences include computer science, physics, neuroscience, genetics, urban transport and engineering, digital humanities, social and computational social science. Readers will learn how to use, in a very practical way (i.e., without focusing on theoretical aspects), the algorithms developed by the community and implemented in the free and open-source software muxViz. The data used in the book is available on a dedicated (open and free) site.

Автор: Bianconi, Ginestra (reader In Applied Mathematics, Reader In Applied Mathematics, School Of Mathematical Sciences, Queen Mary University Of London, Uk
Название: Multilayer networks
ISBN: 0192865544 ISBN-13(EAN): 9780192865540
Издательство: Oxford Academ
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Цена: 31670.00 T
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Описание: Multilayer networks has become a central topic in Network Science. The book presents a comprehensive account of this emerging field. Multilayer networks are formed by several networks and include social networks, financial markets, multi-modal transportation systems, infrastructures, molecular networks, and the brain.

Автор: Arindam Chaudhuri
Название: Visual and Text Sentiment Analysis through Hierarchical Deep Learning Networks
ISBN: 9811374732 ISBN-13(EAN): 9789811374739
Издательство: Springer
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Цена: 46570.00 T
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Описание: This book presents the latest research on hierarchical deep learning for multi-modal sentiment analysis. Further, it analyses sentiments in Twitter blogs from both textual and visual content using hierarchical deep learning networks: hierarchical gated feedback recurrent neural networks (HGFRNNs). Several studies on deep learning have been conducted to date, but most of the current methods focus on either only textual content, or only visual content. In contrast, the proposed sentiment analysis model can be applied to any social blog dataset, making the book highly beneficial for postgraduate students and researchers in deep learning and sentiment analysis. The mathematical abstraction of the sentiment analysis model is presented in a very lucid manner. The complete sentiments are analysed by combining text and visual prediction results. The book’s novelty lies in its development of innovative hierarchical recurrent neural networks for analysing sentiments; stacking of multiple recurrent layers by controlling the signal flow from upper recurrent layers to lower layers through a global gating unit; evaluation of HGFRNNs with different types of recurrent units; and adaptive assignment of HGFRNN layers to different timescales. Considering the need to leverage large-scale social multimedia content for sentiment analysis, both state-of-the-art visual and textual sentiment analysis techniques are used for joint visual-textual sentiment analysis. The proposed method yields promising results from Twitter datasets that include both texts and images, which support the theoretical hypothesis.

Автор: Rokia Missaoui; Talel Abdessalem; Matthieu Latapy
Название: Trends in Social Network Analysis
ISBN: 331953419X ISBN-13(EAN): 9783319534190
Издательство: Springer
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Цена: 111790.00 T
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Описание: The book collects contributions from experts worldwide addressing recent scholarship in social network analysis such as influence spread, link prediction, dynamic network biclustering, and delurking.

Автор: Przemys?aw Kazienko; Nitesh Chawla
Название: Applications of Social Media and Social Network Analysis
ISBN: 3319364413 ISBN-13(EAN): 9783319364414
Издательство: Springer
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Цена: 79190.00 T
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Описание: This collection of contributed chapters demonstrates a wide range of applications within two overlapping research domains: social media analysis and social network analysis.

Автор: Burnaev
Название: Analysis of Images, Social Networks and Texts
ISBN: 3031164997 ISBN-13(EAN): 9783031164996
Издательство: Springer
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Цена: 69870.00 T
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Описание: This book constitutes revised selected papers from the thoroughly refereed proceedings of the 10th International Conference on Analysis of Images, Social Networks and Texts, AIST 2021, held in Tbilisi, Georgia, during December 16–18, 2021. The 20 full papers and 5 short papers included in this book were carefully reviewed and selected from 118 submissions. They were organized in topical sections as follows: Invited papers; natural language processing; computer vision; data analysis and machine learning; social network analysis; and theoretical machine learning and optimization.

Автор: ?zyer
Название: Social Media Analysis for Event Detection
ISBN: 3031082419 ISBN-13(EAN): 9783031082412
Издательство: Springer
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Цена: 139750.00 T
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Описание: This book includes chapters which discuss effective and efficient approaches in dealing with various aspects of social media analysis by using machine learning techniques from clustering to deep learning. A variety of theoretical aspects, application domains and case studies are covered to highlight how it is affordable to maximize the benefit of various applications from postings on social media platforms. Social media platforms have significantly influenced and reshaped various social aspects. They have set new means of communication and interaction between people, turning the whole world into a small village where people with internet connect can easily communicate without feeling any barriers. This has attracted the attention of researchers who have developed techniques and tools capable of studying various aspects of posts on social media platforms with main concentration on Twitter. This book addresses challenging applications in this dynamic domain where it is not possible to continue applying conventional techniques in studying social media postings. The content of this book helps the reader in developing own perspective about how to benefit from machine learning techniques in dealing with social media postings and how social media postings may directly influence various applications.

Автор: Uffe B. Kj?rulff; Anders L. Madsen
Название: Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis
ISBN: 1493900293 ISBN-13(EAN): 9781493900299
Издательство: Springer
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Цена: 121110.00 T
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Описание: In a Second Edition offering six new sections, new examples, tables, figures and more, this book shows how to understand, construct, and analyze intelligent systems for decision support based on probabilistic networks. Includes more than 140 examples.

Название: Networks of networks in biology
ISBN: 1108428878 ISBN-13(EAN): 9781108428873
Издательство: Cambridge Academ
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Цена: 54910.00 T
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Описание: Introduces new graph theory techniques for the analysis and integration of multi-type large data sets) in the life sciences. Discussing cutting-edge problems and techniques, this book provides researchers from a wide range of fields with methods for exploiting big heterogeneous data in biology through the concept of `network of networks`.

Автор: Jalal Kawash
Название: Online Social Media Analysis and Visualization
ISBN: 3319135899 ISBN-13(EAN): 9783319135892
Издательство: Springer
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Цена: 102480.00 T
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Описание: The topics cover generating realistic social network topologies, awareness of user activities, topic and trend generation, estimation of user attributes from their social content, behavior detection, mining social content for common trends, identifying and ranking social content sources, building friend-comprehension tools, and many others.