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Big Data Analytics: A Social Network Approach (Studies In Big Data Ser. #66)
by Mrutyunjaya Panda Aboul-Ella Hassanien Ajith AbrahamSocial networking has increased drastically in recent years, resulting in an increased amount of data being created daily. Furthermore, diversity of issues and complexity of the social networks pose a challenge in social network mining. Traditional algorithm software cannot deal with such complex and vast amounts of data, necessitating the development of novel analytic approaches and tools. This reference work deals with social network aspects of big data analytics. It covers theory, practices and challenges in social networking. The book spans numerous disciplines like neural networking, deep learning, artificial intelligence, visualization, e-learning in higher education, e-healthcare, security and intrusion detection.
Big Data Analytics: A Practical Guide for Managers
by Kim H. Pries Robert DunniganWith this book, managers and decision makers are given the tools to make more informed decisions about big data purchasing initiatives. Big Data Analytics: A Practical Guide for Managers not only supplies descriptions of common tools, but also surveys the various products and vendors that supply the big data market.Comparing and contrasting the dif
Big Data Analytics: Methods and Applications
by Saumyadipta Pyne B. L. S. Prakasa Rao S. B. RaoThis book has a collection of articles written by Big Data experts to describe some of the cutting-edge methods and applications from their respective areas of interest, and provides the reader with a detailed overview of the field of Big Data Analytics as it is practiced today. The chapters cover technical aspects of key areas that generate and use Big Data such as management and finance; medicine and healthcare; genome, cytome and microbiome; graphs and networks; Internet of Things; Big Data standards; bench-marking of systems; and others. In addition to different applications, key algorithmic approaches such as graph partitioning, clustering and finite mixture modelling of high-dimensional data are also covered. The varied collection of themes in this volume introduces the reader to the richness of the emerging field of Big Data Analytics.
Big Data Analytics: 10th International Conference, BDA 2022, Hyderabad, India, December 19–22, 2022, Proceedings (Lecture Notes in Computer Science #13773)
by Partha Pratim Roy Arvind Agarwal Tianrui Li P. Krishna Reddy R. Uday KiranThis book constitutes the proceedings of the 10th International Conference on Big Data Analytics, BDA 2022, which took place in Hyderabad, India, in December 2022.The 7 full papers and 7 short papers presented in this volume were carefully reviewed and selected from 36 submissions. The book also contains 4 keynote talks in full-paper length. The papers are organized in the following topical sections: Big Data Analytics: Vision and Perspectives; Data Science: Architectures; Data Science: Applications; Graph Analytics; Pattern Mining; Predictive Analytics in Agriculture.
Big Data Analytics: Tools and Technology for Effective Planning (Chapman & Hall/CRC Big Data Series)
by Arun K. Somani Ganesh Chandra DekaThe proposed book will discuss various aspects of big data Analytics. It will deliberate upon the tools, technology, applications, use cases and research directions in the field. Chapters would be contributed by researchers, scientist and practitioners from various reputed universities and organizations for the benefit of readers.
Big Data Analytics: Tools and Technology for Effective Planning (Chapman & Hall/CRC Big Data Series)
by Arun K. Somani Ganesh Chandra DekaThe proposed book will discuss various aspects of big data Analytics. It will deliberate upon the tools, technology, applications, use cases and research directions in the field. Chapters would be contributed by researchers, scientist and practitioners from various reputed universities and organizations for the benefit of readers.
Big Data Analytics: First International Conference, BDA 2012, New Delhi, India, December 24-26, 2012, Proceedings (Lecture Notes in Computer Science #7678)
by Srinath Srinivasa Vasudha BhatnagarThis book constitutes the refereed proceedings of the First International Conference on Big Data Analytics, BDA 2012, held in New Delhi, India, in December 2012. The 5 regular papers and 5 short papers presented were carefully reviewed and selected from 42 submissions. The volume also contains two tutorial papers in the section perspectives on big data analytics. The regular contributions are organized in topical sections on: data analytics applications; knowledge discovery through information extraction; and data models in analytics.
Big Data Analytics: Third International Conference, BDA 2014, New Delhi, India, December 20-23, 2014. Proceedings (Lecture Notes in Computer Science #8883)
by Srinath Srinivasa Sameep MehtaThis book constitutes the refereed conference proceedings of the Third International Conference on Big Data Analytics, BDA 2014, held in New Delhi, India, in December 2014. The 11 revised full papers and 6 short papers were carefully reviewed and selected from 35 submissions and cover topics on media analytics; geospatial big data; semantics and data models; search and retrieval; graphics and visualization; application-specific big data.
Big Data Analytics: 9th International Conference, BDA 2021, Virtual Event, December 15-18, 2021, Proceedings (Lecture Notes in Computer Science #13147)
by Satish Narayana Srirama Jerry Chun-Wei Lin Raj Bhatnagar Sonali Agarwal P. Krishna ReddyThis book constitutes the proceedings of the 8th International Conference on Big Data Analytics, BDA 2021, which took place during December 2021. Due to COVID-19 pandemic the conference was held virtually. The 16 full and 3 short papers included in this volume were carefully reviewed and selected from 41 submissions. The contributions were organized in topical sections named as follows: medical and health applications; machine/deep learning; IoTs, sensors, and networks; fundamentation; pattern mining and data analytics.
Big Data Analytics and Artificial Intelligence Against COVID-19: Innovation Vision and Approach (Studies in Big Data #78)
by Aboul-Ella Hassanien Nilanjan Dey Sally ElghamrawyThis book includes research articles and expository papers on the applications of artificial intelligence and big data analytics to battle the pandemic. In the context of COVID-19, this book focuses on how big data analytic and artificial intelligence help fight COVID-19. The book is divided into four parts. The first part discusses the forecasting and visualization of the COVID-19 data. The second part describes applications of artificial intelligence in the COVID-19 diagnosis of chest X-Ray imaging. The third part discusses the insights of artificial intelligence to stop spread of COVID-19, while the last part presents deep learning and big data analytics which help fight the COVID-19.
Big-Data Analytics and Cloud Computing: Theory, Algorithms and Applications
by Marcello Trovati Richard Hill Ashiq Anjum Shao Ying Zhu Lu LiuThis book reviews the theoretical concepts, leading-edge techniques and practical tools involved in the latest multi-disciplinary approaches addressing the challenges of big data. Illuminating perspectives from both academia and industry are presented by an international selection of experts in big data science. Topics and features: describes the innovative advances in theoretical aspects of big data, predictive analytics and cloud-based architectures; examines the applications and implementations that utilize big data in cloud architectures; surveys the state of the art in architectural approaches to the provision of cloud-based big data analytics functions; identifies potential research directions and technologies to facilitate the realization of emerging business models through big data approaches; provides relevant theoretical frameworks, empirical research findings, and numerous case studies; discusses real-world applications of algorithms and techniques to address the challenges of big datasets.
Big Data Analytics and Computational Intelligence for Cybersecurity (Studies in Big Data #111)
by Mariya Ouaissa Zakaria Boulouard Mariyam Ouaissa Inam Ullah Khan Mohammed KaosarThis book presents a collection of state-of-the-art artificial intelligence and big data analytics approaches to cybersecurity intelligence. It illustrates the latest trends in AI/ML-based strategic defense mechanisms against malware, vulnerabilities, cyber threats, as well as proactive countermeasures. It also introduces other trending technologies, such as blockchain, SDN, and IoT, and discusses their possible impact on improving security. The book discusses the convergence of AI/ML and big data in cybersecurity by providing an overview of theoretical, practical, and simulation concepts of computational intelligence and big data analytics used in different approaches of security. It also displays solutions that will help analyze complex patterns in user data and ultimately improve productivity. This book can be a source for researchers, students, and practitioners interested in the fields of artificial intelligence, cybersecurity, data analytics, and recent trends of networks.
Big Data Analytics and Intelligence: A Perspective for Health Care
by Poonam Tanwar, Vishal Jain, Chuan-Ming Liu, Vishal GoyalBig data is a field of research that is growing rapidly, and as the Covid-19 crisis has shown, health care is an area that could benefit greatly from its increased use and application. Big data, as derived partly from the internet of things and analysed according to specific algorithms, has a large and beneficial role to play in preventative medicine, in monitoring the health of specific groups, and in improving diagnostics. Big Data Analytics and Intelligence: A Perspective for Health Care focuses on various areas of health care, ranging from nutrition to cancer, and providing diverse perspectives on all of them. This book explores the entire life-cycle of big data, from information retrieval to analysis, and it shows how big data’s applications can enhance, streamline and improve services for patients and health-care professionals. Each chapter focuses on a specific area of health care and how big data is applicable to it, with background and current examples provided.
Big Data Analytics and Intelligence: A Perspective for Health Care
by Poonam Tanwar Vishal Jain Chuan-Ming Liu Vishal GoyalBig data is a field of research that is growing rapidly, and as the Covid-19 crisis has shown, health care is an area that could benefit greatly from its increased use and application. Big data, as derived partly from the internet of things and analysed according to specific algorithms, has a large and beneficial role to play in preventative medicine, in monitoring the health of specific groups, and in improving diagnostics. Big Data Analytics and Intelligence: A Perspective for Health Care focuses on various areas of health care, ranging from nutrition to cancer, and providing diverse perspectives on all of them. This book explores the entire life-cycle of big data, from information retrieval to analysis, and it shows how big data’s applications can enhance, streamline and improve services for patients and health-care professionals. Each chapter focuses on a specific area of health care and how big data is applicable to it, with background and current examples provided.
Big Data Analytics and Intelligent Systems for Cyber Threat Intelligence
by Yassine Maleh Mamoun Alazab Loai Tawalbeh Imed RomdhaniIn recent years, a considerable amount of effort has been devoted to cyber-threat protection of computer systems which is one of the most critical cybersecurity tasks for single users and businesses since even a single attack can result in compromised data and sufficient losses. Massive losses and frequent attacks dictate the need for accurate and timely detection methods. Current static and dynamic methods do not provide efficient detection, especially when dealing with zero-day attacks. For this reason, big data analytics and machine intelligencebased techniques can be used. This book brings together researchers in the field of big data analytics and intelligent systems for cyber threat intelligence CTI and key data to advance the mission of anticipating, prohibiting, preventing, preparing, and responding to internal security. The wide variety of topics it presents offers readers multiple perspectives on various disciplines related to big data analytics and intelligent systems for cyber threat intelligence applications. Technical topics discussed in the book include:• Big data analytics for cyber threat intelligence and detection• Artificial intelligence analytics techniques• Real-time situational awareness• Machine learning techniques for CTI• Deep learning techniques for CTI• Malware detection and prevention techniques• Intrusion and cybersecurity threat detection and analysis• Blockchain and machine learning techniques for CTI
Big Data Analytics and Intelligent Systems for Cyber Threat Intelligence
by Yassine Maleh Mamoun Alazab Loai Tawalbeh Imed RomdhaniIn recent years, a considerable amount of effort has been devoted to cyber-threat protection of computer systems which is one of the most critical cybersecurity tasks for single users and businesses since even a single attack can result in compromised data and sufficient losses. Massive losses and frequent attacks dictate the need for accurate and timely detection methods. Current static and dynamic methods do not provide efficient detection, especially when dealing with zero-day attacks. For this reason, big data analytics and machine intelligencebased techniques can be used. This book brings together researchers in the field of big data analytics and intelligent systems for cyber threat intelligence CTI and key data to advance the mission of anticipating, prohibiting, preventing, preparing, and responding to internal security. The wide variety of topics it presents offers readers multiple perspectives on various disciplines related to big data analytics and intelligent systems for cyber threat intelligence applications. Technical topics discussed in the book include:• Big data analytics for cyber threat intelligence and detection• Artificial intelligence analytics techniques• Real-time situational awareness• Machine learning techniques for CTI• Deep learning techniques for CTI• Malware detection and prevention techniques• Intrusion and cybersecurity threat detection and analysis• Blockchain and machine learning techniques for CTI
Big Data Analytics and Knowledge Discovery: 23rd International Conference, DaWaK 2021, Virtual Event, September 27–30, 2021, Proceedings (Lecture Notes in Computer Science #12925)
by Matteo Golfarelli Robert Wrembel Gabriele Kotsis A Min Tjoa Ismail KhalilThis volume LNCS 12925 constitutes the papers of the 23rd International Conference on Big Data Analytics and Knowledge Discovery, held in September 2021. Due to COVID-19 pandemic it was held virtually. The 12 full papers presented together with 15 short papers in this volume were carefully reviewed and selected from a total of 71 submissions.The papers reflect a wide range of topics in the field of data integration, data warehousing, data analytics, and recently big data analytics, in a broad sense. The main objectives of this event are to explore, disseminate, and exchange knowledge in these fields.
Big Data Analytics and Knowledge Discovery: 26th International Conference, DaWaK 2024, Naples, Italy, August 26–28, 2024, Proceedings (Lecture Notes in Computer Science #14912)
by Ismail Khalil A Min Tjoa Robert Wrembel Silvia Chiusano Gabriele KotsisThis book constitutes the proceedings of the 26th International Conference on Big Data Analytics and Knowledge Discovery, DaWaK 2024, which too place in Naples, Italy, during August 26-28, 2024. The 16 full and 20 short papers included in this book were carefully reviewed and selected from 83 submissions. They were organized in topical sections as follows: Modeling and design; entity matching and similarity; classification; machine learning methods and applications; time series; data repositories;optimization; and data quality and applications.
Big Data Analytics and Knowledge Discovery: 19th International Conference, DaWaK 2017, Lyon, France, August 28–31, 2017, Proceedings (Lecture Notes in Computer Science #10440)
by Ladjel Bellatreche and Sharma ChakravarthyThis book constitutes the refereed proceedings of the 19th International Conference on Big Data Analytics and Knowledge Discovery, DaWaK 2017, held in Lyon, France, in August 2017.The 24 revised full papers and 11 short papers presented were carefully reviewed and selected from 97 submissions. The papers are organized in the following topical sections: new generation data warehouses design; cloud and NoSQL databases; advanced programming paradigms; non-functional requirements satisfaction; machine learning; social media and twitter analysis; sentiment analysis and user influence; knowledge discovery; and data flow management and optimization.
Big Data Analytics and Knowledge Discovery: 17th International Conference, DaWaK 2015, Valencia, Spain, September 1-4, 2015, Proceedings (Lecture Notes in Computer Science #9263)
by Sanjay Madria Takahiro HaraThis book constitutes the refereed proceedings of the 17th International Conference on Data Warehousing and Knowledge Discovery, DaWaK 2015, held in Valencia, Spain, September 2015.The 31 revised full papers presented were carefully reviewed and selected from 90 submissions. The papers are organized in topical sections similarity measure and clustering; data mining; social computing; heterogeneos networks and data; data warehouses; stream processing; applications of big data analysis; and big data.
Big Data Analytics and Knowledge Discovery: 18th International Conference, DaWaK 2016, Porto, Portugal, September 6-8, 2016, Proceedings (Lecture Notes in Computer Science #9829)
by Sanjay Madria Takahiro HaraThis book constitutes the refereed proceedings of the 18th International Conference on Data Warehousing and Knowledge Discovery, DaWaK 2016, held in Porto, Portugal, September 2016. The 25 revised full papers presented were carefully reviewed and selected from 73 submissions. The papers are organized in topical sections on Mining Big Data, Applications of Big Data Mining, Big Data Indexing and Searching, Big Data Learning and Security, Graph Databases and Data Warehousing, Data Intelligence and Technology.
Big Data Analytics and Knowledge Discovery: 20th International Conference, DaWaK 2018, Regensburg, Germany, September 3–6, 2018, Proceedings (Lecture Notes in Computer Science #11031)
by Carlos Ordonez Ladjel BellatrecheThis book constitutes the refereed proceedings of the 20th International Conference on Big Data Analytics and Knowledge Discovery, DaWaK 2018, held in Regensburg, Germany, in September 2018.The 13 revised full papers and 17 short papers presented were carefully reviewed and selected from 76 submissions. The papers are organized in the following topical sections: Graph analytics; case studies; classification and clustering; pre-processing; sequences; cloud and database systems; and data mining.
Big Data Analytics and Knowledge Discovery: 21st International Conference, DaWaK 2019, Linz, Austria, August 26–29, 2019, Proceedings (Lecture Notes in Computer Science #11708)
by Carlos Ordonez Il-Yeol Song Gabriele Anderst-Kotsis A Min Tjoa Ismail KhalilThis book constitutes the refereed proceedings of the 21st International Conference on Big Data Analytics and Knowledge Discovery, DaWaK 2019, held in Linz, Austria, in September 2019. The 12 full papers and 10 short papers presented were carefully reviewed and selected from 61 submissions. The papers are organized in the following topical sections: Applications; patterns; RDF and streams; big data systems; graphs and machine learning; databases.
Big Data Analytics and Knowledge Discovery: 22nd International Conference, DaWaK 2020, Bratislava, Slovakia, September 14–17, 2020, Proceedings (Lecture Notes in Computer Science #12393)
by Min Song Il-Yeol Song Gabriele Kotsis A Min Tjoa Ismail KhalilThe volume LNCS 12393 constitutes the papers of the 22nd International Conference Big Data Analytics and Knowledge Discovery which will be held online in September 2020. The 15 full papers presented together with 14 short papers plus 1 position paper in this volume were carefully reviewed and selected from a total of 77 submissions. This volume offers a wide range to following subjects on theoretical and practical aspects of big data analytics and knowledge discovery as a new generation of big data repository, data pre-processing, data mining, text mining, sequences, graph mining, and parallel processing.
Big Data Analytics and Knowledge Discovery: 24th International Conference, DaWaK 2022, Vienna, Austria, August 22–24, 2022, Proceedings (Lecture Notes in Computer Science #13428)
by Robert Wrembel Johann Gamper Gabriele Kotsis A Min Tjoa Ismail KhalilThis volume LNCS 13428 constitutes the papers of the 24 th International Conference on Big Data Analytics and Knowledge Discovery, held in August 2022 in Vienna, Austria. The 12 full papers presented together with 12 short papers in this volume were carefully reviewed and selected from a total of 57 submissions. The papers reflect a wide range of topics in the field of data integration, data warehousing, data analytics, and recently big data analytics, in a broad sense. The main objectives of this event are to explore, disseminate, and exchange knowledge in these fields.