الصفحة 4
الصفحة 4
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Network Analysis : Methodological Foundations

‘Network’ is a heavily overloaded term, so that ‘network analysis’ means different things to different people. Specific forms of network analysis are used in the study of diverse structures such as the Internet, interlocking directorates, transportation systems, epidemic spreading, metabolic pathways, the Web graph, electrical circuits, project plans, and so on. There is, however, a broad methodological foundation which is quickly becoming a prerequisite for researchers and practitioners working with network models. From a computer science perspective, network analysis is applied graph theory. Unlike standard graph theory books, the content of this book is organized according to methods for specific levels of analysis (element, group, network) rather than abstract concepts like paths, matchings, or spanning subgraphs. Its topics therefore range from vertex centrality to graph clustering and the evolution of scale-free networks. In 15 coherent chapters, this monograph-like tutorial book introduces and surveys the concepts and methods that drive network analysis, and is thus the first book to do so from a methodological perspective independent of specific application areas.

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Nature Inspired Problem-Solving Methods in Knowledge Engineering ; 2nd International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2007, La Manga del Mar Menor, Spain, June 18-21, 2007, Proceedings, Part II

The second of a two-volume set, this book constitutes the refereed proceedings of the Second International Work-Conference on the Interplay between Natural and Artificial Computation, IWINAC 2007, held in La Manga del Mar Menor, Spain in June 2007.

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Natural Language Processing and Chinese Computing ; 9th CCF International Conference, NLPCC 2020, Zhengzhou, China, October 14–18, 2020, Proceedings, Part II

This two-volume set of LNAI 12340 and LNAI 12341 constitutes the refereed proceedings of the 9th CCF Conference on Natural Language Processing and Chinese Computing, NLPCC 2020, held in Zhengzhou, China, in October 2020. The 70 full papers, 30 poster papers and 14 workshop papers presented were carefully reviewed and selected from 320 submissions. They are organized in the following areas: Conversational Bot/QA; Fundamentals of NLP; Knowledge Base, Graphs and Semantic Web; Machine Learning for NLP; Machine Translation and Multilinguality; NLP Applications; Social Media and Network; Text Mining; and Trending Topics.

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Natural language processing and chinese computing ; 9th CCF International conference, NLPCC 2020, Zhengzhou, China, October 14–18, 2020, Proceedings, Part I

This two-volume set of LNAI 12340 and LNAI 12341 constitutes the refereed proceedings of the 9th CCF Conference on Natural Language Processing and Chinese Computing, NLPCC 2020, held in Zhengzhou, China, in October 2020. The 70 full papers, 30 poster papers and 14 workshop papers presented were carefully reviewed and selected from 320 submissions. They are organized in the following areas: Conversational Bot/QA; Fundamentals of NLP; Knowledge Base, Graphs and Semantic Web; Machine Learning for NLP; Machine Translation and Multilinguality; NLP Applications; Social Media and Network; Text Mining; and Trending Topics.

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Natural language and information systems ; 13th International Conference on Applications of Natural Language to Information Systems, NLDB 2008 London, UK, June 24-27, 2008 Proceedings

This volume contains the papers presented at NLDB 2008, the 13th Inter- tional Conference on Natural Language and Information Systems, held June 25-27,2008.It also containssome of the best researchproposalsas submitted to the NLDB2008 doctoral symposium heldonJune24,2008.Theprogrammealso includes three invited talks covering the main perspectives of the application of naturallanguageto informationsystems: the wayhumansprocess, communicate and understand natural language, what are the implications and challenges - wardssemanticsearchfor the new Webgeneration, how naturallanguageapplies to the well-established database way of querying as a means to unlock data and information for end users.

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Multi-processor system-on-chip 1 : Architectures

covers the key components of MPSoC: processors, memory, interconnect and interfaces. It describes advance features of these components and technologies to build efficient MPSoC architectures. All the main components are detailed: use of memory and their technology, communication support and consistency, and specific processor architectures for general purposes or for dedicated applications.

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Multiple-Aspect Analysis of Semantic Trajectories ; First International Workshop, MASTER 2019, Held in Conjunction with ECML-PKDD 2019, Würzburg, Germany, September 16, 2019, Proceedings

This book constitutes the refereed post-conference proceedings of the First International Workshop on Multiple-Aspect Analysis of Semantic Trajectories, MASTER 2019, held in conjunction with the 19th European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2019, in Würzburg, Germany, in September 2019.

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Multiple Classifier Systems ; 7th International Workshop, MCS 2007, Prague, Czech Republic, May 23-25, 2007, Proceedings

These proceedings are a record of the Multiple Classifier Systems Workshop, MCS 2007, held at the Institute of Information Theory and Automation, Czech Academy of Sciences, Prague in May 2007. the workshop achieved its objective of bringing together researchers from diverse communities (neural networks, pattern rec- nition, machine learning and statistics) concerned with this research topic.

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Multiple Classifier Systems ; 2nd International Workshop, MCS 2001 Cambridge, UK, July 2-4, 2001 Proceedings

Driven by the requirements of a large number of practical and commercially - portant applications, the last decade has witnessed considerable advances in p- tern recognition. Better understanding of the design issues and new paradigms, such as the Support Vector Machine, have contributed to the development of - proved methods of pattern classi cation. However, while any performance gains are welcome, and often extremely signi cant from the practical point of view, it is increasingly more challenging to reach the point of perfection as de ned by the theoretical optimality of decision making in a given decision framework. The asymptoticity of gains that can be made for a single classi er is a re?- tion of the fact that any particular design, regardless of how good it is, simply provides just one estimate of the optimal decision rule.

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Multimodal Processing and Interaction : Audio, Video, Text

Multimodal Processing and Interaction: Audio, Video and Text presents high quality, state-of-the-art research ideas and results from theoretic, algorithmic and application viewpoints. This edited volume contains both state-of-the-art reviews and original contributions by leading experts in the scientific and technological field of multimedia. It grew out of a four-year collaboration among research groups participating in the European network of Excellence on Multimedia Understanding, Semantics, Computation and Learning (MUSCLE).

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Multimedia technology and enhanced learning ; 2nd EAI International conference, ICMTEL 2020, Leicester, UK, April 10-11, 2020, Proceedings, Part II

This two-volume book constitutes the refereed proceedings of the Second International Conference on Multimedia Technology and Enhanced Learning, ICMTEL 2020, held in Leicester, United Kingdom, in April 2020. Due to the COVID-19 pandemic all papers were presented in YouTubeLive. The 83 revised full papers have been selected from 158 submissions. They describe new learning technologies which range from smart school, smart class and smart learning at home and which have been developed from new technologies such as machine learning, multimedia and Internet of Things.

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Multimedia Technology and Enhanced Learning ; 2nd EAI International Conference, ICMTEL 2020, Leicester, UK, April 10-11, 2020, Proceedings, Part I

This two-volume book constitutes the refereed proceedings of the Second International Conference on Multimedia Technology and Enhanced Learning, ICMTEL 2020, held in Leicester, United Kingdom, in April 2020. Due to the COVID-19 pandemic all papers were presented in YouTubeLive. The 83 revised full papers have been selected from 158 submissions. They describe new learning technologies which range from smart school, smart class and smart learning at home and which have been developed from new technologies such as machine learning, multimedia and Internet of Things.

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Multimedia Content Analysis and Mining ; International Workshop, MCAM 2007, Weihai, China, June 30-July 1, 2007, Proceedings

The workshop gives a snapshot of the current wor- wide research in multimedia analysis. Through recent advances in computing, networking, and data storage, multimedia will create new interesting technical possibilities in a wide range of ?elds, such as entertainment, commerce, science, medicine, and public safety.

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Multi-Agent Systems and Applications ; 9th ECCAI Advanced Course ACAI 2001 and Agent Link's 3rd European Agent Systems Summer School, EASSS 2001, Prague, Czech Republic, July 2-13, 2001. Selected Tutorial Papers

The Advanced Course on Artificial Intelligence ACAI 2001 with the subtitle M ulti- Agent Systems and Their Applications , held in Prague, Czech Republic, was a joint event of ECCAI (the European Coordinating Committee for Artificial Intelligence) and AgentLink, the European Network of Excellence for Agent-Based Computing. Whereas ECCAI organizes two-week ACAI courses on different topics every second year, AgentLink s European Agent Systems Summer School (EASSS) has been an annual event since 1999. This year, both of these important events were merged together, giving weight to the fact that multi-agent systems currently represent one of the hottest topics in AI research. The name, ACAI 2001 Summer School, is intended to emphasize that this event continues the tradition of regular ECCAI activities (ACAI), as well as the EASSS summer schools of AgentLink.

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Multiagent System Technologies ; 6th German Conference, MATES 2008, Kaiserslautern, Germany, September 23-26, 2008. Proceedings

This book constitutes the refereed proceedings of the 6th German Conference on Multiagent Systems Technologies, MATES 2008, held in Kaiserslautern, Germany, in September 2008 - co-located with the 31st German Conference on Artificial Intelligence, KI 2008.The 16 revised full papers presented together with 2 invited talks were carefully reviewed and selected from 35 submissions. The papers present and discuss the latest advances of research and development in the area of autonomous agents and multiagent systems ranging from theoretical and methodological issues to applications in various fields.

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Multiaccess, Reservations & Queues

Reservation procedures constitute the core of many popular data transmission protocols. They consist of two steps: A request phase in which a station reserves the communication channel and a transmission phase in which the actual data transmission takes place. Such procedures are often applied in communication networks that are characterised by a shared communication channel with large round-trip times.In this book, we propose queuing models for situations that require a reservation procedure and validate their applicability in the context of cable networks.

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Multi-access Edge Computing : Software Development at the Network Edge

The book aims not only at providing a comprehensive technology and standard reference overview for students, but also useful research insights and practical exercises for edge software developers and investigators in the area (and for students looking to apply their skills). A particular emphasis is given Multi-access Edge Computing (MEC) as defined in European Telecommunications Standards Institute (ETSI), in relationship with other standard organizations like 3GPP, thus in alignment with the recent industry efforts to produce harmonized standards for edge computing leveraging both ETSI ISG MEC and 3GPP specifications.

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Moving Wearables into the Mainstream : Taming the Borg

Moving Wearables into the Mainstream also introduces concepts such as Operational Inertia that form a mindset conducive to designing wearables suitable for broad adoption by consumers. This book provides insight into legal and cultural issues potentially unfamiliar to research engineers, as well as a broad discussion of technologies underlying wearable devices.Moving Wearables into the Mainstream is designed for a professional audience of practitioners and researchers in industry. This volume is also suitable as a secondary advanced-level text or reference book for students in computer science and electrical engineering.

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Modern socio-technical perspectives on privacy

This book provides researchers and professionals with a foundational understanding of online privacy as well as insight into the socio-technical privacy issues that are most pertinent to modern information systems, covering several modern topics (e.g., privacy in social media, IoT) and underexplored areas (e.g., privacy accessibility, privacy for vulnerable populations, cross-cultural privacy).

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Modern deep learning for tabular data : Novel approaches to common modeling problems

Synthesizes and presents novel deep learning approaches to a seemingly unlikely domain - tabular data. Whether for finance, business, security, medicine, or countless other domain, deep learning can help mine and model complex patterns in tabular data - an incredibly ubiquitous form of structured data. Part I of the book offers a rigorous overview of machine learning principles, algorithms, and implementation skills relevant to holistically modeling and manipulating tabular data. Part II studies five dominant deep learning model designs - Artificial Neural Networks, Convolutional Neural Networks, Recurrent Neural Networks, Attention and Transformers, and Tree-Rooted Networks - through both their 'default' usage and their application to tabular data. Part III compounds the power of the previously covered methods by surveying strategies and techniques to supercharge deep learning systems: autoencoders, deep data generation, meta-optimization, multi-model arrangement, and neural network interpretability.

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