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Computational Data and Social Networks
  • Language: en
  • Pages: 551

Computational Data and Social Networks

This book constitutes the refereed proceedings of the 9th International Conference on Computational Data and Social Networks, CSoNet 2020, held in Dallas, TX, USA, in December 2020. The 20 full papers were carefully reviewed and selected from 83 submissions. Additionally the book includes 22 special track papers and 3 extended abstracts. The selected papers are devoted to topics such as Combinatorial Optimization and Learning; Computational Methods for Social Good Applications; NLP and Affective Computing; Privacy and Security; Blockchain; Fact-Checking, Fake News and Malware Detection in Online Social Networks; and Information Spread in Social and Data Networks.

Computational Data and Social Networks
  • Language: en
  • Pages: 380

Computational Data and Social Networks

This book constitutes the refereed proceedings of the 8th International Conference on Computational Data and Social Networks, CSoNet 2019, held in Ho Chi Minh City, Vietnam, in November 2019. The 22 full and 8 short papers presented in this book were carefully reviewed and selected from 120 submissions. The papers appear under the following topical headings: Combinatorial Optimization and Learning; Influence Modeling, Propagation, and Maximization; NLP and Affective Computing; Computational Methods for Social Good; and User Profiling and Behavior Modeling.

Computational Data and Social Networks
  • Language: en
  • Pages: 554

Computational Data and Social Networks

  • Type: Book
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  • Published: 2018-12-11
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  • Publisher: Springer

This book constitutes the refereed proceedings of the 7th International Conference on Computational Data and Social Networks, CSoNet 2018, held in Shanghai, China, in December 2018. The 44 revised full papers presented in this book toghether with 2 extended abstracts, were carefully reviewed and selected from 106 submissions. The topics cover the fundamental background, theoretical technology development, and real-world applications associated with complex and data network analysis, minimizing in uence of rumors on social networks, blockchain Markov modelling, fraud detection, data mining, internet of things (IoT), internet of vehicles (IoV), and others.

Handbook of Trustworthy Federated Learning
  • Language: en
  • Pages: 425

Handbook of Trustworthy Federated Learning

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Computational Data and Social Networks
  • Language: en
  • Pages: 392

Computational Data and Social Networks

This book constitutes the refereed proceedings of the 10th International Conference on Computational Data and Social Networks, CSoNet 2021, which was held online during November 15-17, 2021. The conference was initially planned to take place in Montreal, Quebec, Canada, but changed to an online event due to the COVID-19 pandemic. The 24 full and 8 short papers included in this book were carefully reviewed and selected from 57 submissions. They were organized in topical sections as follows: Combinatorial optimization and learning; deep learning and applications to complex and social systems; measurements of insight from data; complex networks analytics; special track on fact-checking, fake news and malware detection in online social networks; and special track on information spread in social and data networks.

Neural Information Processing
  • Language: en
  • Pages: 772

Neural Information Processing

The two-volume set CCIS 1516 and 1517 constitutes thoroughly refereed short papers presented at the 28th International Conference on Neural Information Processing, ICONIP 2021, held in Sanur, Bali, Indonesia, in December 2021.* The volume also presents papers from the workshop on Artificial Intelligence and Cyber Security, held during the ICONIP 2021. The 176 short and workshop papers presented in this volume were carefully reviewed and selected for publication out of 1093 submissions. The papers are organized in topical sections as follows: theory and algorithms; AI and cybersecurity; cognitive neurosciences; human centred computing; advances in deep and shallow machine learning algorithms for biomedical data and imaging; reliable, robust, and secure machine learning algorithms; theory and applications of natural computing paradigms; applications. * The conference was held virtually due to the COVID-19 pandemic.

Knowledge Discovery, Knowledge Engineering and Knowledge Management
  • Language: en
  • Pages: 409

Knowledge Discovery, Knowledge Engineering and Knowledge Management

  • Type: Book
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  • Published: 2018-11-13
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  • Publisher: Springer

This book constitutes the thoroughly refereed proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, IC3K 2016, held in Porto, Portugal, in November 2016. The 18 full papers presented were carefully reviewed and selected from 186 submissions. The papers are organized in topical sections on knowledge discovery and information retrieval; knowledge engineering and ontology development; and knowledge management and information sharing.

Machine Learning and Knowledge Discovery in Databases
  • Language: en
  • Pages: 898

Machine Learning and Knowledge Discovery in Databases

  • Type: Book
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  • Published: 2017-12-29
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  • Publisher: Springer

The three volume proceedings LNAI 10534 – 10536 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2017, held in Skopje, Macedonia, in September 2017. The total of 101 regular papers presented in part I and part II was carefully reviewed and selected from 364 submissions; there are 47 papers in the applied data science, nectar and demo track. The contributions were organized in topical sections named as follows: Part I: anomaly detection; computer vision; ensembles and meta learning; feature selection and extraction; kernel methods; learning and optimization, matrix and tensor factorization; networks and graphs; neural networks and deep learning. Part II: pattern and sequence mining; privacy and security; probabilistic models and methods; recommendation; regression; reinforcement learning; subgroup discovery; time series and streams; transfer and multi-task learning; unsupervised and semisupervised learning. Part III: applied data science track; nectar track; and demo track.

Phương pháp giải toán từ cơ bản đến nâng cao Đại Số 9- Tập 2
  • Language: vi
  • Pages: 430

Phương pháp giải toán từ cơ bản đến nâng cao Đại Số 9- Tập 2

Đặt mua sách in Zalo: 0918.972.605 FREE SHIP- Thanh toán tại nhà- Mở sách ra xem trước khi thanh toán. Hổ trợ file WORD có Thầy(Cô) giáo. MỤC LỤC Chương III: HỆ PHƯƠNG TRÌNH BẬC NHẤT HAI ẨN Trang 5: Chủ đề 1: GIẢI HỆ PHƯƠNG TRÌNH BẬC NHẤT HAI ẨN Dạng 1: Phương pháp thế(5) Dạng 2: Phương pháp cộng đại số(12) Dạng 3: Phương pháp đồ thị hàm số(19) Dạng 4: Phương pháp dùng máy CASIO 580VNX(23) Dạng 5: Bài tập luyện tập(26) Trang 28: Chủ đề 2: Giải hệ phương trình bằng phương pháp đặt ẩn phụ Trang 40: Chủ đề 3: Các dạng toán quy về giải hệ Dạng 1: Gia...

New Frontiers in Mining Complex Patterns
  • Language: en
  • Pages: 268

New Frontiers in Mining Complex Patterns

  • Type: Book
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  • Published: 2017-07-01
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  • Publisher: Springer

This book features a collection of revised and significantly extended versions of the papers accepted for presentation at the 5th International Workshop on New Frontiers in Mining Complex Patterns, NFMCP 2016, held in conjunction with ECML-PKDD 2016 in Riva del Garda, Italy, in September 2016. The book is composed of five parts: feature selection and induction; classification prediction; clustering; pattern discovery; applications.