9 results on '"streaming analytics"'
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2. Assessing the Dependability of Apache Spark System: Streaming Analytics on Large-Scale Ocean Data
- Author
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Dahal, Janak, Ioup, Elias, Arifuzzaman, Shaikh, Abdelguerfi, Mahdi, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Kotenko, Igor, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Barbosa, Simone Diniz Junqueira, Editorial Board Member, Wang, Guojun, editor, Bhuiyan, Md Zakirul Alam, editor, De Capitani di Vimercati, Sabrina, editor, and Ren, Yizhi, editor
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- 2019
- Full Text
- View/download PDF
3. Streaming Analytics—Real-Time Customer Satisfaction in Brick-and-Mortar Retailing
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Weber, Felix, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, and Silhavy, Radek, editor
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- 2019
- Full Text
- View/download PDF
4. Streaming Analytics
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Turaga, Deepak, Liu, Ling, editor, and Özsu, M. Tamer, editor
- Published
- 2018
- Full Text
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5. A Tool of Benchmarking Realtime Analysis for Massive Behavior Data
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Teng, Mingyan, Sun, Qiao, Deng, Buqiao, Sun, Lei, Qin, Xiongpai, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Chen, Lei, editor, Jensen, Christian S., editor, Shahabi, Cyrus, editor, Yang, Xiaochun, editor, and Lian, Xiang, editor
- Published
- 2017
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6. Process Mining Workshops
- Author
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Montali, Marco, Senderovich, Arik, and Weidlich, Matthias
- Subjects
process mining ,process discovery ,process analytics ,process querying ,conformance checking ,predictive process monitoring ,data science ,knowledge graphs ,event data ,streaming analytics ,machine learning ,deep learning ,business process management ,health informatics ,thema EDItEUR::U Computing and Information Technology::UN Databases::UNF Data mining ,thema EDItEUR::K Economics, Finance, Business and Management::KJ Business and Management::KJQ Business mathematics and systems ,thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQM Machine learning ,thema EDItEUR::U Computing and Information Technology::UB Information technology: general topics ,thema EDItEUR::U Computing and Information Technology::UB Information technology: general topics::UBH Digital and information technologies: Health and safety aspects - Abstract
This open access book constitutes revised selected papers from the International Workshops held at the 4th International Conference on Process Mining, ICPM 2022, which took place in Bozen-Bolzano, Italy, during October 23–28, 2022. The conference focuses on the area of process mining research and practice, including theory, algorithmic challenges, and applications. The co-located workshops provided a forum for novel research ideas. The 42 papers included in this volume were carefully reviewed and selected from 89 submissions. They stem from the following workshops: – 3rd International Workshop on Event Data and Behavioral Analytics (EDBA) – 3rd International Workshop on Leveraging Machine Learning in Process Mining (ML4PM) – 3rd International Workshop on Responsible Process Mining (RPM) (previously known as Trust, Privacy and Security Aspects in Process Analytics) – 5th International Workshop on Process-Oriented Data Science for Healthcare (PODS4H) – 3rd International Workshop on Streaming Analytics for Process Mining (SA4PM) – 7th International Workshop on Process Querying, Manipulation, and Intelligence (PQMI) – 1st International Workshop on Education meets Process Mining (EduPM) – 1st International Workshop on Data Quality and Transformation in Process Mining (DQT-PM)
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- 2023
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7. Process Mining Workshops. ICPM 2022 International Workshops, Bozen-Bolzano, Italy, October 23-28, 2022, Revised Selected Papers.
- Author
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Montali, Marco, Montali, Marco, Senderovich, Arik, and Weidlich, Matthias
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Business mathematics & systems ,Data mining ,Health & safety aspects of IT ,Information technology: general issues ,Machine learning ,business process management ,conformance checking ,data science ,deep learning ,event data ,health informatics ,knowledge graphs ,machine learning ,predictive process monitoring ,process analytics ,process discovery ,process mining ,process querying ,streaming analytics - Abstract
Summary: This open access book constitutes revised selected papers from the International Workshops held at the 4th International Conference on Process Mining, ICPM 2022, which took place in Bozen-Bolzano, Italy, during October 23-28, 2022. The conference focuses on the area of process mining research and practice, including theory, algorithmic challenges, and applications. The co-located workshops provided a forum for novel research ideas. The 42 papers included in this volume were carefully reviewed and selected from 89 submissions. They stem from the following workshops: - 3rd International Workshop on Event Data and Behavioral Analytics (EDBA) - 3rd International Workshop on Leveraging Machine Learning in Process Mining (ML4PM) - 3rd International Workshop on Responsible Process Mining (RPM) (previously known as Trust, Privacy and Security Aspects in Process Analytics) - 5th International Workshop on Process-Oriented Data Science for Healthcare (PODS4H) - 3rd International Workshop on Streaming Analytics for Process Mining (SA4PM) - 7th International Workshop on Process Querying, Manipulation, and Intelligence (PQMI) - 1st International Workshop on Education meets Process Mining (EduPM) - 1st International Workshop on Data Quality and Transformation in Process Mining (DQT-PM)
8. Process Mining Workshops
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Munoz-Gama, Jorge and Lu, Xixi
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Process Mining ,Process Discovery ,Process Analytics ,Process Querying ,Conformance Checking ,Predictive Process Monitoring ,Data Science ,Event Data ,Streaming Analytics ,Machine Learning ,Decision Support Systems ,Business Process Management ,Information Systems ,Petri Nets ,Open Access ,bic Book Industry Communication::U Computing & information technology::UN Databases::UNF Data mining ,bic Book Industry Communication::K Economics, finance, business & management::KJ Business & management::KJQ Business mathematics & systems ,bic Book Industry Communication::U Computing & information technology::UB Information technology: general issues - Abstract
This open access book constitutes revised selected papers from the International Workshops held at the Third International Conference on Process Mining, ICPM 2021, which took place in Eindhoven, The Netherlands, during October 31–November 4, 2021. The conference focuses on the area of process mining research and practice, including theory, algorithmic challenges, and applications. The co-located workshops provided a forum for novel research ideas. The 28 papers included in this volume were carefully reviewed and selected from 65 submissions. They stem from the following workshops: 2nd International Workshop on Event Data and Behavioral Analytics (EDBA) 2nd International Workshop on Leveraging Machine Learning in Process Mining (ML4PM) 2nd International Workshop on Streaming Analytics for Process Mining (SA4PM) 6th International Workshop on Process Querying, Manipulation, and Intelligence (PQMI) 4th International Workshop on Process-Oriented Data Science for Healthcare (PODS4H) 2nd International Workshop on Trust, Privacy, and Security in Process Analytics (TPSA) One survey paper on the results of the XES 2.0 Workshop is included.
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- 2022
- Full Text
- View/download PDF
9. Scalable Real-Time DDoS Traffic Monitoring and Characterization
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Huyn, Joojay
- Subjects
- Computer science, Apache Spark, Big Data Analytics, DDoS Detection, DDoS Monitoring, Network Security, Streaming Analytics
- Abstract
High volume DDoS attacks continue to cause serious financial losses and damage to company reputations, despite years of research in preventing and mitigating them. Many proposed techniques for handling these attacks assume that the attack has already been detected and its traffic properly characterized; yet, existing methods of detecting and characterizing such attacks have not been widely adopted, for various reasons. We describe a scalable real-time DDoS monitoring system that leverages modern big data technologies to effectively analyze high volume DDoS attacks. Evaluated on multiple large-scale traffic datasets that capture recent real-world DDoS attacks and synthetic traffic based on sophisticated attack characteristics, our approach detects and characterizes these attacks quickly and accurately. Furthermore, we show that our monitoring system 1) clearly justifies its decisions resulting from explainable analysis of input traffic volume metrics, thus increasing monitoring transparency and facilitating the diagnosis and debugging of monitoring performance for network security teams 2) leverages identified attack characteristics to separate benign from malicious traffic and send helpful defense recommendations, the identified attack characteristics and malicious traffic traces, to downstream DDoS traffic filtering systems.
- Published
- 2018
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