Visual Analysis of Multilayer Networks, McGee Fintan, Renoust Benjamin, Archambault Daniel
Автор: McGee Fintan, Renoust Benjamin, Archambault Daniel Название: Visual Analysis of Multilayer Networks ISBN: 1636391435 ISBN-13(EAN): 9781636391434 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 9563.00 р. Наличие на складе: Поставка под заказ.
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.
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: Dmitry I. Ignatov; Mikhail Yu. Khachay; Valeri G. Название: Analysis of Images, Social Networks and Texts ISBN: 3319529196 ISBN-13(EAN): 9783319529196 Издательство: Springer Рейтинг: Цена: 9146.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book constitutes the proceedings of the 5th International Conference on Analysis of Images, Social Networks and Texts, AIST 2016, held in Yekaterinburg, Russia, in April 2016.The 23 full papers, 7 short papers, and 3 industrial papers were carefully reviewed and selected from 142 submissions.
Автор: Wil M. P. van der Aalst; Vladimir Batagelj; Goran Название: Analysis of Images, Social Networks and Texts ISBN: 3030110265 ISBN-13(EAN): 9783030110260 Издательство: Springer Рейтинг: Цена: 6097.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book constitutes the proceedings of the 7th International Conference on Analysis of Images, Social Networks and Texts, AIST 2018, held in Moscow, Russia, in July 2018.The 29 full papers were carefully reviewed and selected from 107 submissions (of which 26 papers were rejected without being reviewed). The papers are organized in topical sections on natural language processing; analysis of images and video; general topics of data analysis; analysis of dynamic behavior through event data; optimization problems on graphs and network structures; and innovative systems.
Описание: This book constitutes the proceedings of the 8th International Conference on Analysis of Images, Social Networks and Texts, AIST 2019, held in Kazan, Russia, in July 2019.The 24 full papers and 10 short papers were carefully reviewed and selected from 134 submissions (of which 21 papers were rejected without being reviewed).
Описание: This book provides a comprehensive guide for practitioners who wish to understand, construct, and analyze intelligent systems for decision support based on probabilistic networks. The theory and methods presented are illustrated through more than 140 examples.
Автор: van der Aalst Название: Analysis of Images, Social Networks and Texts ISBN: 3319730126 ISBN-13(EAN): 9783319730127 Издательство: Springer Рейтинг: Цена: 6097.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book constitutes the proceedings of the 6th International Conference on Analysis of Images, Social Networks and Texts, AIST 2017, held in Moscow, Russia, in July 2017. The 29 full papers and 8 short papers were carefully reviewed and selected from 127 submissions. general topics of data analysis;
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.
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.
Автор: Rokia Missaoui; Sergei O. Kuznetsov; Sergei Obiedk Название: Formal Concept Analysis of Social Networks ISBN: 3319877399 ISBN-13(EAN): 9783319877396 Издательство: Springer Рейтинг: Цена: 12196.00 р. Наличие на складе: Нет в наличии.
Автор: Dmitry I. Ignatov; Mikhail Yu. Khachay; Alexander Название: Analysis of Images, Social Networks and Texts ISBN: 3319125796 ISBN-13(EAN): 9783319125794 Издательство: Springer Рейтинг: Цена: 7074.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book constitutes the proceedings of the Third International Conference on Analysis of Images, Social Networks and Texts, AIST 2014, held in Yekaterinburg, Russia, in April 2014. They are presented together with 3 short industrial papers, 4 invited papers and tutorials. The papers deal with topics such as analysis of images and videos;
Автор: Rokia Missaoui; Sergei O. Kuznetsov; Sergei Obiedk Название: Formal Concept Analysis of Social Networks ISBN: 3319641662 ISBN-13(EAN): 9783319641669 Издательство: Springer Рейтинг: Цена: 13415.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The book studies the existing and potential connections between Social Network Analysis (SNA) and Formal Concept Analysis (FCA) by showing how standard SNA techniques, usually based on graph theory, can be supplemented by FCA methods, which rely on lattice theory.The book presents contributions to the following areas: acquisition of terminological knowledge from social networks, knowledge communities, individuality computation, other types of FCA-based analysis of bipartite graphs (two-mode networks), multimodal clustering, community detection and description in one-mode and multi-mode networks, adaptation of the dual-projection approach to weighted bipartite graphs, extensions to the Kleinberg's HITS algorithm as well as attributed graph analysis.
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