Download or read book A Novel Anomaly Detection Scheme Based on Principal Component Classifier written by and published by . This book was released on 2003 with total page 9 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper proposes a novel scheme that uses robust principal component classifier in intrusion detection problems where the training data may be unsupervised. Assuming that anomalies can be treated as outliers, an intrusion predictive model is constructed from the major and minor principal components of the normal instances. A measure of the difference of an anomaly from the normal instance is the distance in the principal component space. The distance based on the major components that account for 50% of the total variation and the minor components whose eigenvalues less than 0.20 is shown to work well. The experiments with KDD Cup 1999 data demonstrate that the proposed method achieves 98.94% in recall and 97.89% in precision with the false alarm rate 0.92% and outperforms the nearest neighbor method, density-based local outliers (LOF) approach, and the outlier detection algorithm based on Canberra metric.
Download or read book ECAI 2020 written by G. De Giacomo and published by IOS Press. This book was released on 2020-09-11 with total page 3122 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the proceedings of the 24th European Conference on Artificial Intelligence (ECAI 2020), held in Santiago de Compostela, Spain, from 29 August to 8 September 2020. The conference was postponed from June, and much of it conducted online due to the COVID-19 restrictions. The conference is one of the principal occasions for researchers and practitioners of AI to meet and discuss the latest trends and challenges in all fields of AI and to demonstrate innovative applications and uses of advanced AI technology. The book also includes the proceedings of the 10th Conference on Prestigious Applications of Artificial Intelligence (PAIS 2020) held at the same time. A record number of more than 1,700 submissions was received for ECAI 2020, of which 1,443 were reviewed. Of these, 361 full-papers and 36 highlight papers were accepted (an acceptance rate of 25% for full-papers and 45% for highlight papers). The book is divided into three sections: ECAI full papers; ECAI highlight papers; and PAIS papers. The topics of these papers cover all aspects of AI, including Agent-based and Multi-agent Systems; Computational Intelligence; Constraints and Satisfiability; Games and Virtual Environments; Heuristic Search; Human Aspects in AI; Information Retrieval and Filtering; Knowledge Representation and Reasoning; Machine Learning; Multidisciplinary Topics and Applications; Natural Language Processing; Planning and Scheduling; Robotics; Safe, Explainable, and Trustworthy AI; Semantic Technologies; Uncertainty in AI; and Vision. The book will be of interest to all those whose work involves the use of AI technology.
Download or read book The International Conference on Advanced Machine Learning Technologies and Applications AMLTA2019 written by Aboul Ella Hassanien and published by Springer. This book was released on 2019-03-16 with total page 960 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the peer-reviewed proceedings of the 4th International Conference on Advanced Machine Learning Technologies and Applications (AMLTA 2019), held in Cairo, Egypt, on March 28–30, 2019, and organized by the Scientific Research Group in Egypt (SRGE). The papers cover the latest research on machine learning, deep learning, biomedical engineering, control and chaotic systems, text mining, summarization and language identification, machine learning in image processing, renewable energy, cyber security, and intelligence swarms and optimization.
Download or read book Advanced Information Networking and Applications written by Leonard Barolli and published by Springer Nature. This book was released on with total page 514 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Smart Cities written by Houbing Song and published by John Wiley & Sons. This book was released on 2017-06-21 with total page 872 pages. Available in PDF, EPUB and Kindle. Book excerpt: Provides the foundations and principles needed for addressing the various challenges of developing smart cities Smart cities are emerging as a priority for research and development across the world. They open up significant opportunities in several areas, such as economic growth, health, wellness, energy efficiency, and transportation, to promote the sustainable development of cities. This book provides the basics of smart cities, and it examines the possible future trends of this technology. Smart Cities: Foundations, Principles, and Applications provides a systems science perspective in presenting the foundations and principles that span multiple disciplines for the development of smart cities. Divided into three parts—foundations, principles, and applications—Smart Cities addresses the various challenges and opportunities of creating smart cities and all that they have to offer. It also covers smart city theory modeling and simulation, and examines case studies of existing smart cities from all around the world. In addition, the book: Addresses how to develop a smart city and how to present the state of the art and practice of them all over the world Focuses on the foundations and principles needed for advancing the science, engineering, and technology of smart cities—including system design, system verification, real-time control and adaptation, Internet of Things, and test beds Covers applications of smart cities as they relate to smart transportation/connected vehicle (CV) and Intelligent Transportation Systems (ITS) for improved mobility, safety, and environmental protection Smart Cities: Foundations, Principles, and Applications is a welcome reference for the many researchers and professionals working on the development of smart cities and smart city-related industries.
Download or read book Foundations and Novel Approaches in Data Mining written by Tsau Young Lin and published by Springer Science & Business Media. This book was released on 2005-11-03 with total page 398 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data-mining has become a popular research topic in recent years for the treatment of the "data rich and information poor" syndrome. Currently, application oriented engineers are only concerned with their immediate problems, which results in an ad hoc method of problem solving. Researchers, on the other hand, lack an understanding of the practical issues of data-mining for real-world problems and often concentrate on issues that are of no significance to the practitioners. In this volume, we hope to remedy problems by (1) presenting a theoretical foundation of data-mining, and (2) providing important new directions for data-mining research. A set of well respected data mining theoreticians were invited to present their views on the fundamental science of data mining. We have also called on researchers with practical data mining experiences to present new important data-mining topics.
Download or read book Artificial Intelligence in Medicine written by Martin Michalowski and published by Springer Nature. This book was released on 2020-09-25 with total page 505 pages. Available in PDF, EPUB and Kindle. Book excerpt: The LNAI 12299 constitutes the papers of the 18th International Conference on Artificial Intelligence in Medicine, AIME 2020, which will be held online in August 2020. The 42 full papers presented together with 1short papers in this volume were carefully reviewed and selected from a total of 103 submissions. The AIME 2020 goals were to present and consolidate the international state of the art of AI in biomedical research from the perspectives of theory, methodology, systems, and applications.
Download or read book Data Mining written by Charu C. Aggarwal and published by Springer. This book was released on 2015-04-13 with total page 746 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook explores the different aspects of data mining from the fundamentals to the complex data types and their applications, capturing the wide diversity of problem domains for data mining issues. It goes beyond the traditional focus on data mining problems to introduce advanced data types such as text, time series, discrete sequences, spatial data, graph data, and social networks. Until now, no single book has addressed all these topics in a comprehensive and integrated way. The chapters of this book fall into one of three categories: Fundamental chapters: Data mining has four main problems, which correspond to clustering, classification, association pattern mining, and outlier analysis. These chapters comprehensively discuss a wide variety of methods for these problems. Domain chapters: These chapters discuss the specific methods used for different domains of data such as text data, time-series data, sequence data, graph data, and spatial data. Application chapters: These chapters study important applications such as stream mining, Web mining, ranking, recommendations, social networks, and privacy preservation. The domain chapters also have an applied flavor. Appropriate for both introductory and advanced data mining courses, Data Mining: The Textbook balances mathematical details and intuition. It contains the necessary mathematical details for professors and researchers, but it is presented in a simple and intuitive style to improve accessibility for students and industrial practitioners (including those with a limited mathematical background). Numerous illustrations, examples, and exercises are included, with an emphasis on semantically interpretable examples. Praise for Data Mining: The Textbook - “As I read through this book, I have already decided to use it in my classes. This is a book written by an outstanding researcher who has made fundamental contributions to data mining, in a way that is both accessible and up to date. The book is complete with theory and practical use cases. It’s a must-have for students and professors alike!" -- Qiang Yang, Chair of Computer Science and Engineering at Hong Kong University of Science and Technology "This is the most amazing and comprehensive text book on data mining. It covers not only the fundamental problems, such as clustering, classification, outliers and frequent patterns, and different data types, including text, time series, sequences, spatial data and graphs, but also various applications, such as recommenders, Web, social network and privacy. It is a great book for graduate students and researchers as well as practitioners." -- Philip S. Yu, UIC Distinguished Professor and Wexler Chair in Information Technology at University of Illinois at Chicago
Download or read book Hybrid Artificial Intelligent Systems written by Pablo García Bringas and published by Springer Nature. This book was released on 2023-08-28 with total page 789 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 18th International Conference on Hybrid Artificial Intelligent Systems, HAIS 2023, held in Salamanca, Spain, during September 5–7, 2023. The 65 full papers included in this book were carefully reviewed and selected from 120 submissions. They were organized in topical sections as follows: Anomaly and Fault Detection, Data Mining and Decision Support Systems, Deep Learning, Evolutionary Computation and Optimization, HAIS Applications, Image and Speech Signal Processing, Agents and Multiagents, Biomedical Applicatons.
Download or read book KI 2021 Advances in Artificial Intelligence written by Stefan Edelkamp and published by Springer Nature. This book was released on 2021-09-29 with total page 389 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 44th German Conference on Artificial Intelligence, KI 2021, held in September/October 2021. Due to COVID-19 pandemic the conference was held virtually. The 16 full and 4 short papers with one extended abstract were carefully reviewed and selected from 59 submissions. As well-established annual conference series KI is dedicated to research on theory and applications across all methods and topic areas of AI research.
Download or read book Monitoring and Securing Virtualized Networks and Services written by Anna Sperotto and published by Springer. This book was released on 2014-06-25 with total page 207 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 8th IFIP WG 6.6 International Conference on Monitoring and Securing Virtualized Networks and Services, AIMS 2014, held in Brno, Czech Republic, in June/July 2014. The 9 full papers presented were carefully reviewed and selected from 29 submissions. The volume also includes 13 papers presented at the AIMS Ph.D. workshop. They were reviewed and selected from 27 submissions. The full papers are organized in topical sections on emerging infrastructures for networks and services; experimental studies for security management; and monitoring methods for quality-of-service and security. The workshop papers are organized in topical sections on management of virtualized network resources and functions; security management; SDN and content delivery; monitoring and information sharing.
Download or read book Machine Learning and Knowledge Discovery in Databases written by Massih-Reza Amini and published by Springer Nature. This book was released on 2023-03-16 with total page 768 pages. Available in PDF, EPUB and Kindle. Book excerpt: The multi-volume set LNAI 13713 until 13718 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2022, which took place in Grenoble, France, in September 2022. The 236 full papers presented in these proceedings were carefully reviewed and selected from a total of 1060 submissions. In addition, the proceedings include 17 Demo Track contributions. The volumes are organized in topical sections as follows: Part I: Clustering and dimensionality reduction; anomaly detection; interpretability and explainability; ranking and recommender systems; transfer and multitask learning; Part II: Networks and graphs; knowledge graphs; social network analysis; graph neural networks; natural language processing and text mining; conversational systems; Part III: Deep learning; robust and adversarial machine learning; generative models; computer vision; meta-learning, neural architecture search; Part IV: Reinforcement learning; multi-agent reinforcement learning; bandits and online learning; active and semi-supervised learning; private and federated learning; . Part V: Supervised learning; probabilistic inference; optimal transport; optimization; quantum, hardware; sustainability; Part VI: Time series; financial machine learning; applications; applications: transportation; demo track.
Download or read book Quantitative Evaluation of Systems written by Javier Campos and published by Springer. This book was released on 2015-08-21 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 12th International Conference on Quantitative Evaluation of Systems, QEST 2015, held in Madrid, Spain, in September 2015. The 19 papers presented were carefully reviewed and selected from 42 submissions. They are organized in topical sections named: modelling and applications; tools; petri nets, process algebra and fault trees; applications; and queuing systems and hybrid systems. The book also contains one full-paper invited talk.
Download or read book Outlier Analysis written by Charu C. Aggarwal and published by Springer. This book was released on 2016-12-10 with total page 481 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides comprehensive coverage of the field of outlier analysis from a computer science point of view. It integrates methods from data mining, machine learning, and statistics within the computational framework and therefore appeals to multiple communities. The chapters of this book can be organized into three categories: Basic algorithms: Chapters 1 through 7 discuss the fundamental algorithms for outlier analysis, including probabilistic and statistical methods, linear methods, proximity-based methods, high-dimensional (subspace) methods, ensemble methods, and supervised methods. Domain-specific methods: Chapters 8 through 12 discuss outlier detection algorithms for various domains of data, such as text, categorical data, time-series data, discrete sequence data, spatial data, and network data. Applications: Chapter 13 is devoted to various applications of outlier analysis. Some guidance is also provided for the practitioner. The second edition of this book is more detailed and is written to appeal to both researchers and practitioners. Significant new material has been added on topics such as kernel methods, one-class support-vector machines, matrix factorization, neural networks, outlier ensembles, time-series methods, and subspace methods. It is written as a textbook and can be used for classroom teaching.
Download or read book Outlier Ensembles written by Charu C. Aggarwal and published by Springer. This book was released on 2017-04-06 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses a variety of methods for outlier ensembles and organizes them by the specific principles with which accuracy improvements are achieved. In addition, it covers the techniques with which such methods can be made more effective. A formal classification of these methods is provided, and the circumstances in which they work well are examined. The authors cover how outlier ensembles relate (both theoretically and practically) to the ensemble techniques used commonly for other data mining problems like classification. The similarities and (subtle) differences in the ensemble techniques for the classification and outlier detection problems are explored. These subtle differences do impact the design of ensemble algorithms for the latter problem. This book can be used for courses in data mining and related curricula. Many illustrative examples and exercises are provided in order to facilitate classroom teaching. A familiarity is assumed to the outlier detection problem and also to generic problem of ensemble analysis in classification. This is because many of the ensemble methods discussed in this book are adaptations from their counterparts in the classification domain. Some techniques explained in this book, such as wagging, randomized feature weighting, and geometric subsampling, provide new insights that are not available elsewhere. Also included is an analysis of the performance of various types of base detectors and their relative effectiveness. The book is valuable for researchers and practitioners for leveraging ensemble methods into optimal algorithmic design.
Download or read book Computer Vision ECCV 2024 written by Aleš Leonardis and published by Springer Nature. This book was released on with total page 579 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Analysis of Machine Learning Techniques for Intrusion Detection System A Review written by Asghar Ali Shah and published by Infinite Study. This book was released on with total page 11 pages. Available in PDF, EPUB and Kindle. Book excerpt: Security is a key issue to both computer and computer networks. Intrusion detection System (IDS) is one of the major research problems in network security. IDSs are developed to detect both known and unknown attacks. There are many techniques used in IDS for protecting computers and networks from network based and host based attacks. Various Machine learning techniques are used in IDS. This study analyzes machine learning techniques in IDS. It also reviews many related studies done in the period from 2000 to 2012 and it focuses on machine learning techniques. Related studies include single, hybrid, ensemble classifiers, baseline and datasets used.
