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    Applied Graph Data Science

Applied Graph Data Science

Applied Graph Data Science
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      Applied Graph Data Science: Graph Algorithms and Platforms, Knowledge Graphs, Neural Networks, and Applied Use Cases delineates how graph data science significantly empowers the application of data science. The book discusses the emerging paradigm of graph data science in detail along with its practical research and real-world applications. Readers will be enriched with the knowledge of graph data science, graph analytics, algorithms, databases, platforms, and use cases across a variety of research and topics and applications. This book also presents how graphs are used as a programming language, especially demonstrating how Sleptsov Net Computing can contribute as an entirely graphical concurrent processing language for supercomputers. Graph data science is emerging as an expressive and illustrative data structure for optimally representing a variety of data types and their insightful relationships. These data structures include graph query languages, databases, algorithms, and platforms. From here, powerful analytics methods and machine learning/deep learning (ML/DL) algorithms are quickly evolving to analyze and make sense out of graph data. As a result, ground-breaking use cases across scientific research topics and industry verticals are being developed using graph data representation and manipulation. A wide range of complex business and scientific research requirements are efficiently represented and solved through graph data analysis, and Applied Graph Data Science: Graph Algorithms and Platforms, Knowledge Graphs, Neural Networks, and Applied Graph Data Science gives readers both the conceptual foundations and technical methods for applying these powerful techniques.
      Format: CONTRIBUTORS: Applied Graph Data Science EAN: 9780443296543 COUNTRY: United States PAGES: 250 WEIGHT: 450 g HEIGHT: 235 cm
      PUBLISHED BY: Elsevier Science & Technology DATE PUBLISHED: 2025-02-01 CITY: GENRE: COMPUTERS / Data Science / General WIDTH: 191 cm SPINE:

      Book Themes:

      Data capture and analysis

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      Pethuru Raj PhD works as chief architect and vice president of site reliability engineering (SRE) division of Reliance Jio Infocomm. Ltd. Bangalore. Previously he worked as a cloud infrastructure architect in the IBM Global Cloud Center of Excellence (CoE), Bangalore. He worked as a TOGAF-certified enterprise architecture (EA) consultant in Wipro Consulting Services (WCS) Division and as a lead architect in the corporate research (CR) division of Robert Bosch, India. He has gained more than 18 years of IT industry experience. He finished the CSIR-sponsored PhD degree in Anna University, Chennai and continued the UGC-sponsored postdoctoral research in the department of Computer Science and Automation, Indian Institute of Science, Bangalore. Thereafter, he was granted a couple of international research fellowships (JSPS and JST) to work as a research scientist for 3.5 years in two leading Japanese universities. He has authored and edited 18 books thus far and he focuses on some of the emerging technologies such as Containerized Clouds; Big, Fast, and Streaming Data Analytics; Microservices architecture (MSA); Machine and Deep Learning Algorithms; Blockchain Technology; The Internet of Things; and Edge Computing. He has published more than 30 research papers in peer-reviewed journals such as IEEE, ACM, Springer-Verlag, Inderscience, etc. Pushan Kumar Dutta is a distinguished Assistant Professor Grade III at Amity University Kolkata, specializing in Electronics and Communication Engineering. He holds a PhD from Jadavpur University and completed a postdoctorate with scholarship from Erasmus Mundus Association at the University of Oradea, Romania. Dr. Dutta has an extensive research background with diverse interests including data mining, AI, edge computing, predictive analytics, and earthquake precursor study. His expertise is recognized globally through keynote speeches delivered at international events like the Data Science Europe summit. In addition to his academic pursuits, Dr. Dutta actively mentors’ students and coordinates sports and innovation competitions at Amity University Kolkata. He teaches classes on IoT (Internet of Things), robotics, and engineering while being involved in various technical programming committees for prestigious conferences worldwide. Furthermore, his achievements include receiving the ATAL NITI Aayog Mentor of Change recognition from NITI Aayog (National Institution for Transforming India). Under his guidance, a group won Best Presentation award worth $1000 during Tech Connections session held by Johnson Controls. Dr. Dutta’s passion for education is evident through his copyright entitled 'Innovative Digital Teaching and Learning for Professional Readiness'. Professor Peter Han Joo Chong is the Associate Head of School (Research) at the School of Engineering, Computer and Mathematical Sciences, Auckland University of Technology, New Zealand. Between 2016 and 2021, he was the Head of Department of Electrical and Elect
      Applied Graph Data Science: Graph Algorithms and Platforms, Knowledge Graphs, Neural Networks, and Applied Use Cases delineates how graph data science significantly empowers the application of data science. The book discusses the emerging paradigm of graph data science in detail along with its practical research and real-world applications. Readers will be enriched with the knowledge of graph data science, graph analytics, algorithms, databases, platforms, and use cases across a variety of research and topics and applications. This book also presents how graphs are used as a programming language, especially demonstrating how Sleptsov Net Computing can contribute as an entirely graphical concurrent processing language for supercomputers. Graph data science is emerging as an expressive and illustrative data structure for optimally representing a variety of data types and their insightful relationships. These data structures include graph query languages, databases, algorithms, and platforms. From here, powerful analytics methods and machine learning/deep learning (ML/DL) algorithms are quickly evolving to analyze and make sense out of graph data. As a result, ground-breaking use cases across scientific research topics and industry verticals are being developed using graph data representation and manipulation. A wide range of complex business and scientific research requirements are efficiently represented and solved through graph data analysis, and Applied Graph Data Science: Graph Algorithms and Platforms, Knowledge Graphs, Neural Networks, and Applied Graph Data Science gives readers both the conceptual foundations and technical methods for applying these powerful techniques.
      Format: CONTRIBUTORS: Applied Graph Data Science EAN: 9780443296543 COUNTRY: United States PAGES: 250 WEIGHT: 450 g HEIGHT: 235 cm
      PUBLISHED BY: Elsevier Science & Technology DATE PUBLISHED: 2025-02-01 CITY: GENRE: COMPUTERS / Data Science / General WIDTH: 191 cm SPINE:

      Book Themes:

      Data capture and analysis

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      Be the first to write a review
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      Pethuru Raj PhD works as chief architect and vice president of site reliability engineering (SRE) division of Reliance Jio Infocomm. Ltd. Bangalore. Previously he worked as a cloud infrastructure architect in the IBM Global Cloud Center of Excellence (CoE), Bangalore. He worked as a TOGAF-certified enterprise architecture (EA) consultant in Wipro Consulting Services (WCS) Division and as a lead architect in the corporate research (CR) division of Robert Bosch, India. He has gained more than 18 years of IT industry experience. He finished the CSIR-sponsored PhD degree in Anna University, Chennai and continued the UGC-sponsored postdoctoral research in the department of Computer Science and Automation, Indian Institute of Science, Bangalore. Thereafter, he was granted a couple of international research fellowships (JSPS and JST) to work as a research scientist for 3.5 years in two leading Japanese universities. He has authored and edited 18 books thus far and he focuses on some of the emerging technologies such as Containerized Clouds; Big, Fast, and Streaming Data Analytics; Microservices architecture (MSA); Machine and Deep Learning Algorithms; Blockchain Technology; The Internet of Things; and Edge Computing. He has published more than 30 research papers in peer-reviewed journals such as IEEE, ACM, Springer-Verlag, Inderscience, etc. Pushan Kumar Dutta is a distinguished Assistant Professor Grade III at Amity University Kolkata, specializing in Electronics and Communication Engineering. He holds a PhD from Jadavpur University and completed a postdoctorate with scholarship from Erasmus Mundus Association at the University of Oradea, Romania. Dr. Dutta has an extensive research background with diverse interests including data mining, AI, edge computing, predictive analytics, and earthquake precursor study. His expertise is recognized globally through keynote speeches delivered at international events like the Data Science Europe summit. In addition to his academic pursuits, Dr. Dutta actively mentors’ students and coordinates sports and innovation competitions at Amity University Kolkata. He teaches classes on IoT (Internet of Things), robotics, and engineering while being involved in various technical programming committees for prestigious conferences worldwide. Furthermore, his achievements include receiving the ATAL NITI Aayog Mentor of Change recognition from NITI Aayog (National Institution for Transforming India). Under his guidance, a group won Best Presentation award worth $1000 during Tech Connections session held by Johnson Controls. Dr. Dutta’s passion for education is evident through his copyright entitled 'Innovative Digital Teaching and Learning for Professional Readiness'. Professor Peter Han Joo Chong is the Associate Head of School (Research) at the School of Engineering, Computer and Mathematical Sciences, Auckland University of Technology, New Zealand. Between 2016 and 2021, he was the Head of Department of Electrical and Elect

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