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Author: Mehmet Kaya
Publisher: Springer Nature
ISBN: 3030336980
Category : Science
Languages : en
Pages : 245
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Book Description
This book focusses on recommendation, behavior, and anomaly, among of social media analysis. First, recommendation is vital for a variety of applications to narrow down the search space and to better guide people towards educated and personalized alternatives. In this context, the book covers supporting students, food venue, friend and paper recommendation to demonstrate the power of social media data analysis. Secondly, this book treats behavior analysis and understanding as important for a variety of applications, including inspiring behavior from discussion platforms, determining user choices, detecting following patterns, crowd behavior modeling for emergency evacuation, tracking community structure, etc. Third, fraud and anomaly detection have been well tackled based on social media analysis. This has is illustrated in this book by identifying anomalous nodes in a network, chasing undetected fraud processes, discovering hidden knowledge, detecting clickbait, etc. With this wide coverage, the book forms a good source for practitioners and researchers, including instructors and students.
Author: Mehmet Kaya
Publisher: Springer Nature
ISBN: 3030336980
Category : Science
Languages : en
Pages : 245
Get Book
Book Description
This book focusses on recommendation, behavior, and anomaly, among of social media analysis. First, recommendation is vital for a variety of applications to narrow down the search space and to better guide people towards educated and personalized alternatives. In this context, the book covers supporting students, food venue, friend and paper recommendation to demonstrate the power of social media data analysis. Secondly, this book treats behavior analysis and understanding as important for a variety of applications, including inspiring behavior from discussion platforms, determining user choices, detecting following patterns, crowd behavior modeling for emergency evacuation, tracking community structure, etc. Third, fraud and anomaly detection have been well tackled based on social media analysis. This has is illustrated in this book by identifying anomalous nodes in a network, chasing undetected fraud processes, discovering hidden knowledge, detecting clickbait, etc. With this wide coverage, the book forms a good source for practitioners and researchers, including instructors and students.
Author: Hai-Jew, Shalin
Publisher: IGI Global
ISBN: 1799864987
Category : Education
Languages : en
Pages : 497
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Book Description
On the Social Web, people share their enthusiasms and expertise on almost every topic, and based on this, learners can find resources created by individuals with varying expertise. Through this trend and the wide availability of video cameras and authoring tools, people are creating DIY resources and sharing their knowledge, skills, and abilities broadly. While these resources are increasing in availability, what has not been explored is the effectiveness of these resources, peer-to-peer teaching and learning, and how well this content prepares learners for professional roles. Practical Peer-to-Peer Teaching and Learning on the Social Web explores the efficacies of online teaching and learning with materials by peers and provides insights into what is made available for teaching and learning by the broad public. It also considers intended and unintended outcomes of open-shared learning online and discusses practical ethics in teaching and learning online. Covering topics such as learner roles and instructional design, it is ideal for teachers, instructional designers and developers, software developers, user interface designers, researchers, academicians, and students.
Author: Qi Xuan
Publisher: Springer Nature
ISBN: 981162609X
Category : Computers
Languages : en
Pages : 256
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Book Description
Graph data is powerful, thanks to its ability to model arbitrary relationship between objects and is encountered in a range of real-world applications in fields such as bioinformatics, traffic network, scientific collaboration, world wide web and social networks. Graph data mining is used to discover useful information and knowledge from graph data. The complications of nodes, links and the semi-structure form present challenges in terms of the computation tasks, e.g., node classification, link prediction, and graph classification. In this context, various advanced techniques, including graph embedding and graph neural networks, have recently been proposed to improve the performance of graph data mining. This book provides a state-of-the-art review of graph data mining methods. It addresses a current hot topic – the security of graph data mining – and proposes a series of detection methods to identify adversarial samples in graph data. In addition, it introduces readers to graph augmentation and subgraph networks to further enhance the models, i.e., improve their accuracy and robustness. Lastly, the book describes the applications of these advanced techniques in various scenarios, such as traffic networks, social and technical networks, and blockchains.
Author: IEEE Staff
Publisher:
ISBN: 9781479958788
Category :
Languages : en
Pages :
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Book Description
The IEEE ACM International Conference on Advances in Social Network Analysis and Mining (ASONAM) provides a premier interdisciplinary forum to bring together researchers and practitioners from all social networking analysis and mining related fields for presentation of original research results, as well as exchange and dissemination of innovative, practical development experiences ASONAM 2014 seeks to address important challenging problems with a specific focus on the emerging trends and industry needs associated with social networking analysis and mining The conference solicits experimental and theoretical findings along with their real world applications General areas of interest to ASONAM 2014 include the design, analysis and implementation of social networking theory, systems and applications from computer science, mathematics, communications, business administration, sociology, psychology, anthropology, applied linguistics, biology and medicine
Author: Sun, Zhaohao
Publisher: IGI Global
ISBN: 179989018X
Category : Computers
Languages : en
Pages : 425
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Book Description
Intelligent business analytics is an emerging technology that has become a mainstream market adopted broadly across industries, organizations, and geographic regions. Intelligent business analytics is a current focus for research and development across academia and industries and must be examined and considered thoroughly so businesses can apply the technology appropriately. The Handbook of Research on Foundations and Applications of Intelligent Business Analytics examines the technologies and applications of intelligent business analytics and discusses the foundations of intelligent analytics such as intelligent mining, intelligent statistical modeling, and machine learning. Covering topics such as augmented analytics and artificial intelligence systems, this major reference work is ideal for scholars, engineers, professors, practitioners, researchers, industry professionals, academicians, and students.
Author: Katharina A. Zweig
Publisher: Springer Science & Business Media
ISBN: 3709107415
Category : Computers
Languages : en
Pages : 535
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Book Description
This book presents a perspective of network analysis as a tool to find and quantify significant structures in the interaction patterns between different types of entities. Moreover, network analysis provides the basic means to relate these structures to properties of the entities. It has proven itself to be useful for the analysis of biological and social networks, but also for networks describing complex systems in economy, psychology, geography, and various other fields. Today, network analysis packages in the open-source platform R and other open-source software projects enable scientists from all fields to quickly apply network analytic methods to their data sets. Altogether, these applications offer such a wealth of network analytic methods that it can be overwhelming for someone just entering this field. This book provides a road map through this jungle of network analytic methods, offers advice on how to pick the best method for a given network analytic project, and how to avoid common pitfalls. It introduces the methods which are most often used to analyze complex networks, e.g., different global network measures, types of random graph models, centrality indices, and networks motifs. In addition to introducing these methods, the central focus is on network analysis literacy – the competence to decide when to use which of these methods for which type of question. Furthermore, the book intends to increase the reader's competence to read original literature on network analysis by providing a glossary and intensive translation of formal notation and mathematical symbols in everyday speech. Different aspects of network analysis literacy – understanding formal definitions, programming tasks, or the analysis of structural measures and their interpretation – are deepened in various exercises with provided solutions. This text is an excellent, if not the best starting point for all scientists who want to harness the power of network analysis for their field of expertise.
Author: Hocine Cherifi
Publisher: Springer Nature
ISBN: 3031534727
Category : Computer networks
Languages : en
Pages : 501
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Book Description
This book highlights cutting-edge research in the field of network science, offering scientists, researchers, students and practitioners a unique update on the latest advances in theory and a multitude of applications. It presents the peer-reviewed proceedings of the XII International Conference on Complex Networks and their Applications (COMPLEX NETWORKS 2023). The carefully selected papers cover a wide range of theoretical topics such as network embedding and network geometry; community structure, network dynamics; diffusion, epidemics and spreading processes; machine learning and graph neural networks as well as all the main network applications, including social and political networks; networks in finance and economics; biological networks and technological networks.
Author: Michele Berlingerio
Publisher: Springer
ISBN: 3030109283
Category : Computers
Languages : en
Pages : 866
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Book Description
The three volume proceedings LNAI 11051 – 11053 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2018, held in Dublin, Ireland, in September 2018. The total of 131 regular papers presented in part I and part II was carefully reviewed and selected from 535 submissions; there are 52 papers in the applied data science, nectar and demo track. The contributions were organized in topical sections named as follows: Part I: adversarial learning; anomaly and outlier detection; applications; classification; clustering and unsupervised learning; deep learningensemble methods; and evaluation. Part II: graphs; kernel methods; learning paradigms; matrix and tensor analysis; online and active learning; pattern and sequence mining; probabilistic models and statistical methods; recommender systems; and transfer learning. Part III: ADS data science applications; ADS e-commerce; ADS engineering and design; ADS financial and security; ADS health; ADS sensing and positioning; nectar track; and demo track.
Author: Mehmet Kaya
Publisher: Springer
ISBN: 3030025926
Category : Social Science
Languages : en
Pages : 238
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Book Description
This timely book focuses on influence and behavior analysis in the broader context of social network applications and social media. Twitter accounts of telecommunications companies are analyzed. Rumor sources in finite graphs with boundary effects by message-passing algorithms are identified. The coherent, state-of-the-art collection of chapters was initially selected based on solid reviews from the IEEE/ACM International Conference on Advances in Social Networks, Analysis, and Mining (ASONAM '17). Chapters were then improved and extended substantially, and the final versions were rigorously reviewed and revised to meet the series standards. Original chapters coming from outside of the meeting round out the coverage. The result will appeal to researchers and students working in social network and social media analysis.
Author: Bhatnagar, Vishal
Publisher: IGI Global
ISBN: 1522504907
Category : Computers
Languages : en
Pages : 309
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Book Description
Internet usage has become a normal and essential aspect of everyday life. Due to the immense amount of information available on the web, it has become obligatory to find ways to sift through and categorize the overload of data while removing redundant material. Collaborative Filtering Using Data Mining and Analysis evaluates the latest patterns and trending topics in the utilization of data mining tools and filtering practices. Featuring emergent research and optimization techniques in the areas of opinion mining, text mining, and sentiment analysis, as well as their various applications, this book is an essential reference source for researchers and engineers interested in collaborative filtering.
