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This book constitutes the refereed proceedings of the 19th International Conference on Computing and Combinatorics, COCOON 2013, held in Hangzhou, China, in June 2013. The 56 revised full papers presented were carefully reviewed and selected from 120 submissions. There was a co-organized workshop on discrete algorithms of which 8 short papers were accepted and a workshop on computational social networks where 12 papers out of 25 submissions were accepted.
This book constitutes refereed proceeding of the Second International Cognitive Cities Conference, IC3 2019, held in Kyoto, Japan, in September 2019. The 37 full papers and 46 short papers were thoroughly reviewed and selected from 206 submissions. The papers are organized according to the topical sections on cognitive city for special needs; cognitive city theory, modeling and simulation; XR and educational innovations for cognitive city; educational technology and strategy in cognitive city; safety, security and privacy in cognitive city; artificial intelligence theory and technology related to cognitive city; Internet of Things for cognitive city; business application and management for cognitive city; big data for cognitive city; engineering technology and applied science for cognitive city; maker, CT and STEAM education for cognitive city.
Large-scale, highly interconnected networks, which are often modeled as graphs, pervade both our society and the natural world around us. Uncertainty, on the other hand, is inherent in the underlying data due to a variety of reasons, such as noisy measurements, lack of precise information needs, inference and prediction models, or explicit manipulation, e.g., for privacy purposes. Therefore, uncertain, or probabilistic, graphs are increasingly used to represent noisy linked data in many emerging application scenarios, and they have recently become a hot topic in the database and data mining communities. Many classical algorithms such as reachability and shortest path queries become #P-complete and, thus, more expensive over uncertain graphs. Moreover, various complex queries and analytics are also emerging over uncertain networks, such as pattern matching, information diffusion, and influence maximization queries. In this book, we discuss the sources of uncertain graphs and their applications, uncertainty modeling, as well as the complexities and algorithmic advances on uncertain graphs processing in the context of both classical and emerging graph queries and analytics. We emphasize the current challenges and highlight some future research directions.
The three volume proceedings LNAI 11906 – 11908 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2019, held in Würzburg, Germany, in September 2019. The total of 130 regular papers presented in these volumes was carefully reviewed and selected from 733 submissions; there are 10 papers in the demo track. The contributions were organized in topical sections named as follows: Part I: pattern mining; clustering, anomaly and outlier detection, and autoencoders; dimensionality reduction and feature selection; social networks and graphs; decision trees, interpretability, and causality; strings and streams; privacy and security; optimization. Part II: supervised learning; multi-label learning; large-scale learning; deep learning; probabilistic models; natural language processing. Part III: reinforcement learning and bandits; ranking; applied data science: computer vision and explanation; applied data science: healthcare; applied data science: e-commerce, finance, and advertising; applied data science: rich data; applied data science: applications; demo track. Chapter "Heavy-tailed Kernels Reveal a Finer Cluster Structure in t-SNE Visualisations" is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
This book develops a framework that shows how uncertainty in Artificial Intelligence (AI) expands and generalizes traditional AI. It explores the uncertainties of knowledge and intelligence. The authors focus on the importance of natural language – the carrier of knowledge and intelligence, and introduce efficient physical methods for data mining amd control. In this new edition, we have more in-depth description of the models and methods, of which the mathematical properties are proved strictly which make these theories and methods more complete. The authors also highlight their latest research results.
The three volume proceedings LNAI 11051 – 11053 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2018, held in Dublin, Ireland, in September 2018. The total of 131 regular papers presented in part I and part II was carefully reviewed and selected from 535 submissions; there are 52 papers in the applied data science, nectar and demo track. The contributions were organized in topical sections named as follows: Part I: adversarial learning; anomaly and outlier detection; applications; classification; clustering and unsupervised learning; deep learningensemble methods; and evaluation. Part II: graphs; kernel methods; learning paradigms; matrix and tensor analysis; online and active learning; pattern and sequence mining; probabilistic models and statistical methods; recommender systems; and transfer learning. Part III: ADS data science applications; ADS e-commerce; ADS engineering and design; ADS financial and security; ADS health; ADS sensing and positioning; nectar track; and demo track.
Safety and Reliability of Complex Engineered Systems contains the Proceedings of the 25th European Safety and Reliability Conference, ESREL 2015, held 7-10 September 2015 in Zurich, Switzerland. Including 570 papers on theories and methods in the area of risk, safety and reliability, and their applications to a wide range of industrial, civil and social sectors, this book will be of interest to academics and professionals involved or interested in aspect of risk, safety and reliability in various engineering areas.
This book constitutes the thoroughly refereed post-conference proceedings of the Second International Workshop on Algorithmic Aspects of Cloud Computing, ALGOCLOUD 2016, held in Aarhus, Denmark, in August 2016. The 11 revised full papers presented together with one tutorial paper were carefully reviewed and selected from 30 initial submissions. They deal with the following topics: algorithmic aspects of elasticity and scalability for distributed, large-scale data stores (e.g. NoSQL and columnar databases); search and retrieval algorithms for cloud infrastructures; monitoring and analysis of elasticity for virtualized environments; NoSQL, schemaless data modeling, integration; caching and load-balancing; storage structures and indexing for cloud databases; new algorithmic aspects of parallel and distributed computing for cloud applications; scalable machine learning, analytics and data science; high availability, reliability, failover; transactional models and algorithms for cloud databases; query languages and processing programming models; consistency, replication and partitioning CAP, data structures and algorithms for eventually consistent stores.
This book constitutes the refereed conference proceedings of the 12th EAI International Conference on Quality, Reliability, Security and Robustness in Heterogeneous Networks, QShine 2016, held in Seoul, South Korea, in July 2016. The 27 full papers, 5 short papers and 18 workshop papers were selected from 85 submissions. The papers are organized thematically in tracks, starting with network security, followed by QoS, reliability and modeling, wireless and mobile networks. In addition the papers of two workshops are included: International Workshop on 5G Communication Architecture and Technology (5G-CAT 2016), and the 2nd International Workshop on Sensor Networks and Cloud Computing (SNCC 2016).
This three-volume set, LNAI 10937, 10938, and 10939, constitutes the thoroughly refereed proceedings of the 22nd Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2018, held in Melbourne, VIC, Australia, in June 2018. The 164 full papers were carefully reviewed and selected from 592 submissions. The volumes present papers focusing on new ideas, original research results and practical development experiences from all KDD related areas, including data mining, data warehousing, machine learning, artificial intelligence, databases, statistics, knowledge engineering, visualization, decision-making systems and the emerging applications.