Search results for: network-embedding

Network Embedding

Author : Cheng Yang
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Many machine learning algorithms require real-valued feature vectors of data instances as inputs. By projecting data into vector spaces, representation learning techniques have achieved promising performance in many areas such as computer vision and natural language processing. There is also a need to learn representations for discrete relational data, namely networks or graphs. Network Embedding (NE) aims at learning vector representations for each node or vertex in a network to encode the topologic structure. Due to its convincing performance and efficiency, NE has been widely applied in many network applications such as node classification and link prediction. This book provides a comprehensive introduction to the basic concepts, models, and applications of network representation learning (NRL). The book starts with an introduction to the background and rising of network embeddings as a general overview for readers. Then it introduces the development of NE techniques by presenting several representative methods on general graphs, as well as a unified NE framework based on matrix factorization. Afterward, it presents the variants of NE with additional information: NE for graphs with node attributes/contents/labels; and the variants with different characteristics: NE for community-structured/large-scale/heterogeneous graphs. Further, the book introduces different applications of NE such as recommendation and information diffusion prediction. Finally, the book concludes the methods and applications and looks forward to the future directions.

P2P Networking and Applications

Author : John Buford
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Peer-to-Peer (P2P) networks enable users to directly share digital content (such as audio, video, and text files) as well as real-time data (such as telephony traffic) with other users without depending on a central server. Although originally popularized by unlicensed online music services such as Napster, P2P networking has recently emerged as a viable multimillion dollar business model for the distribution of information, telecommunications, and social networking. Written at an accessible level for any reader familiar with fundamental Internet protocols, the book explains the conceptual operations and architecture underlying basic P2P systems using well-known commercial systems as models and also provides the means to improve upon these models with innovations that will better performance, security, and flexibility. Peer-to-Peer Networking and Applications is thus both a valuable starting point and an important reference to those practitioners employed by any of the 200 companies with approximately $400 million invested in this new and lucrative technology. Uses well-known commercial P2P systems as models, thus demonstrating real-world applicability. Discusses how current research trends in wireless networking, high-def content, DRM, etc. will intersect with P2P, allowing readers to account for future developments in their designs. Provides online access to the Overlay Weaver P2P emulator, an open-source tool that supports a number of peer-to-peer applications with which readers can practice.

Collaborative Computing Networking Applications and Worksharing

Author : Xinheng Wang
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This book constitutes the thoroughly refereed proceedings of the 15th International Conference on Collaborative Computing: Networking, Applications, and Worksharing, CollaborateCom 2019, held in London, UK, in August 2019. The 40 full papers, 8 short papers and 6 workshop presented were carefully reviewed and selected from 121 submissions. The papers reflect the conference sessions as follows: cloud, IoT and edge computing, collaborative IoT services and applications, artificial intelligence, software development, teleportation protocol and entanglement swapping, network based on the neural network, scheme based on blockchain and zero-knowledge proof in vehicle networking, software development.

NETWORKING 2010

Author : Mark Crovella
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This book constitutes the refereed proceedings of the 9th IFIP-TC6 Networking Conference, Networking 2010. Papers were solicited in three broad topic areas: applications and services, network technologies, and internet design. All papers were considered on their merits by a uni?ed Technical ProgramCommittee (TPC); there was no attempt to enforce a quota among topic areas. We believe the resulting program is an excellentrepresentationofthebreadthofrecentadvancesinnetworkingresearch. This year, the conference received 101 full paper submissions from 23 co- trieson?vecontinents,re?ectingastrongdiversityinthenetworkingcommunity. Similarly, the 92 members of the TPC are from 21 countries and include a mix of academic, industry, and governmental a?liations. The TPC members, aided by some 50 external reviewers, provided a total of 470 reviews and follow-up discussions totaling more than 200 messages. The ?nal selections were made at a TPC meeting hosted by Columbia University in New York City, with both in-person and remote participation. In total, authors of accepted papers have academic and industry a?liations in 15 countries. We ?nally selected 24papers for presentationduring the conference technical sessions. A small number of papers were assigned a shepherd from the TPC to assist in paper revision. These statistics represent an acceptance rate of just under 24%, comparable to that of previous years. The TPC also identi?ed several papers that re?ect particularly promising early results; these papers were selected for presentation as work-in-progress papers and are identi?ed as such in the proceedings.

Developing Networks using Artificial Intelligence

Author : Haipeng Yao
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This book mainly discusses the most important issues in artificial intelligence-aided future networks, such as applying different ML approaches to investigate solutions to intelligently monitor, control and optimize networking. The authors focus on four scenarios of successfully applying machine learning in network space. It also discusses the main challenge of network traffic intelligent awareness and introduces several machine learning-based traffic awareness algorithms, such as traffic classification, anomaly traffic identification and traffic prediction. The authors introduce some ML approaches like reinforcement learning to deal with network control problem in this book. Traditional works on the control plane largely rely on a manual process in configuring forwarding, which cannot be employed for today's network conditions. To address this issue, several artificial intelligence approaches for self-learning control strategies are introduced. In addition, resource management problems are ubiquitous in the networking field, such as job scheduling, bitrate adaptation in video streaming and virtual machine placement in cloud computing. Compared with the traditional with-box approach, the authors present some ML methods to solve the complexity network resource allocation problems. Finally, semantic comprehension function is introduced to the network to understand the high-level business intent in this book. With Software-Defined Networking (SDN), Network Function Virtualization (NFV), 5th Generation Wireless Systems (5G) development, the global network is undergoing profound restructuring and transformation. However, with the improvement of the flexibility and scalability of the networks, as well as the ever-increasing complexity of networks, makes effective monitoring, overall control, and optimization of the network extremely difficult. Recently, adding intelligence to the control plane through AI&ML become a trend and a direction of network development This book's expected audience includes professors, researchers, scientists, practitioners, engineers, industry managers, and government research workers, who work in the fields of intelligent network. Advanced-level students studying computer science and electrical engineering will also find this book useful as a secondary textbook.

Computational Science ICCS 2020

Author : Valeria V. Krzhizhanovskaya
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The seven-volume set LNCS 12137, 12138, 12139, 12140, 12141, 12142, and 12143 constitutes the proceedings of the 20th International Conference on Computational Science, ICCS 2020, held in Amsterdam, The Netherlands, in June 2020.* The total of 101 papers and 248 workshop papers presented in this book set were carefully reviewed and selected from 719 submissions (230 submissions to the main track and 489 submissions to the workshops). The papers were organized in topical sections named: Part I: ICCS Main Track Part II: ICCS Main Track Part III: Advances in High-Performance Computational Earth Sciences: Applications and Frameworks; Agent-Based Simulations, Adaptive Algorithms and Solvers; Applications of Computational Methods in Artificial Intelligence and Machine Learning; Biomedical and Bioinformatics Challenges for Computer Science Part IV: Classifier Learning from Difficult Data; Complex Social Systems through the Lens of Computational Science; Computational Health; Computational Methods for Emerging Problems in (Dis-)Information Analysis Part V: Computational Optimization, Modelling and Simulation; Computational Science in IoT and Smart Systems; Computer Graphics, Image Processing and Artificial Intelligence Part VI: Data Driven Computational Sciences; Machine Learning and Data Assimilation for Dynamical Systems; Meshfree Methods in Computational Sciences; Multiscale Modelling and Simulation; Quantum Computing Workshop Part VII: Simulations of Flow and Transport: Modeling, Algorithms and Computation; Smart Systems: Bringing Together Computer Vision, Sensor Networks and Machine Learning; Software Engineering for Computational Science; Solving Problems with Uncertainties; Teaching Computational Science; UNcErtainty QUantIficatiOn for ComputationAl modeLs *The conference was canceled due to the COVID-19 pandemic.

Algorithms and Architectures for Parallel Processing

Author : Xiang-he Sun
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This two volume set LNCS 8630 and 8631 constitutes the proceedings of the 14th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2014, held in Dalian, China, in August 2014. The 70 revised papers presented in the two volumes were selected from 285 submissions. The first volume comprises selected papers of the main conference and papers of the 1st International Workshop on Emerging Topics in Wireless and Mobile Computing, ETWMC 2014, the 5th International Workshop on Intelligent Communication Networks, IntelNet 2014, and the 5th International Workshop on Wireless Networks and Multimedia, WNM 2014. The second volume comprises selected papers of the main conference and papers of the Workshop on Computing, Communication and Control Technologies in Intelligent Transportation System, 3C in ITS 2014, and the Workshop on Security and Privacy in Computer and Network Systems, SPCNS 2014.

Advances in Knowledge Discovery and Data Mining

Author : Dinh Phung
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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.

Computational Science ICCS 2021

Author : Maciej Paszynski
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Proceedings of NetSci X 2020 Sixth International Winter School and Conference on Network Science

Author : Naoki Masuda
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This volume constitutes the proceedings of NetSci-X 2020: the Sixth International School and Conference on Network Science, which was held in Tokyo, Japan, in January 2020. NetSci-X is the Network Science Society’s winter conference series that covers a wide variety of interdisciplinary topics on networks. Participants come from various fields, including (but not limited to): mathematics, physics, computer science, social sciences, management and marketing sciences, organization science, communication science, systems science, biology, ecology, neuroscience, medicine, as well as business. This volume consists of contributed papers that have been accepted to NetSc-X 2020 through a rigorous peer review process. Researchers, students, and professionals will gain first-hand information about today’s cutting-edge research frontier of network science.

Advances in Knowledge Discovery and Data Mining

Author : Kamal Karlapalem
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The 3-volume set LNAI 12712-12714 constitutes the proceedings of the 25th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2021, which was held during May 11-14, 2021. The 157 papers included in the proceedings were carefully reviewed and selected from a total of 628 submissions. They were organized in topical sections as follows: Part I: Applications of knowledge discovery and data mining of specialized data; Part II: Classical data mining; data mining theory and principles; recommender systems; and text analytics; Part III: Representation learning and embedding, and learning from data.

Deep Learning in Natural Language Processing

Author : Li Deng
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In recent years, deep learning has fundamentally changed the landscapes of a number of areas in artificial intelligence, including speech, vision, natural language, robotics, and game playing. In particular, the striking success of deep learning in a wide variety of natural language processing (NLP) applications has served as a benchmark for the advances in one of the most important tasks in artificial intelligence. This book reviews the state of the art of deep learning research and its successful applications to major NLP tasks, including speech recognition and understanding, dialogue systems, lexical analysis, parsing, knowledge graphs, machine translation, question answering, sentiment analysis, social computing, and natural language generation from images. Outlining and analyzing various research frontiers of NLP in the deep learning era, it features self-contained, comprehensive chapters written by leading researchers in the field. A glossary of technical terms and commonly used acronyms in the intersection of deep learning and NLP is also provided. The book appeals to advanced undergraduate and graduate students, post-doctoral researchers, lecturers and industrial researchers, as well as anyone interested in deep learning and natural language processing.

Web Information Systems Engineering WISE 2020

Author : Zhisheng Huang
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This book constitutes the proceedings of the 21st International Conference on Web Information Systems Engineering, WISE 2020, held in Amsterdam, The Netherlands, in October 2020. The 81 full papers presented were carefully reviewed and selected from 190 submissions. The papers are organized in the following topical sections: Part I: network embedding; graph neural network; social network; graph query; knowledge graph and entity linkage; spatial temporal data analysis; and service computing and cloud computing Part II: information extraction; text mining; security and privacy; recommender system; database system and workflow; and data mining and applications.

Network Embedding

Author : Cheng Yang
File Size : 79.11 MB
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Many machine learning algorithms require real-valued feature vectors of data instances as inputs. By projecting data into vector spaces, representation learning techniques have achieved promising performance in many areas such as computer vision and natural language processing. There is also a need to learn representations for discrete relational data, namely networks or graphs. Network Embedding (NE) aims at learning vector representations for each node or vertex in a network to encode the topologic structure. Due to its convincing performance and efficiency, NE has been widely applied in many network applications such as node classification and link prediction. This book provides a comprehensive introduction to the basic concepts, models, and applications of network representation learning (NRL). The book starts with an introduction to the background and rising of network embeddings as a general overview for readers. Then it introduces the development of NE techniques by presenting several representative methods on general graphs, as well as a unified NE framework based on matrix factorization. Afterward, it presents the variants of NE with additional information: NE for graphs with node attributes/contents/labels; and the variants with different characteristics: NE for community-structured/large-scale/heterogeneous graphs. Further, the book introduces different applications of NE such as recommendation and information diffusion prediction. Finally, the book concludes the methods and applications and looks forward to the future directions.

Machine Learning and Knowledge Discovery in Databases

Author : Ulf Brefeld
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Testbeds and Research Infrastructure Development of Networks and Communities

Author : Victor C.M. Leung
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This book constitutes the proceedings of the 9th International Conference on Testbeds and Research Infrastructures for the Development of Networks and Communities, TridentCom 2014, held in Guangzhou, China, in May 2014. The 49 revised full papers presented were carefully selected out of 149 submissions. The conference consisted of 6 symposia covering topics such as testbed virtualization, Internet of Things, vehicular networks, SDN, NDN, large-scale testbed federation, mobile networks, wireless networks.

Data Driven Modeling of Cyber Physical Systems using Side Channel Analysis

Author : Sujit Rokka Chhetri
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This book provides a new perspective on modeling cyber-physical systems (CPS), using a data-driven approach. The authors cover the use of state-of-the-art machine learning and artificial intelligence algorithms for modeling various aspect of the CPS. This book provides insight on how a data-driven modeling approach can be utilized to take advantage of the relation between the cyber and the physical domain of the CPS to aid the first-principle approach in capturing the stochastic phenomena affecting the CPS. The authors provide practical use cases of the data-driven modeling approach for securing the CPS, presenting novel attack models, building and maintaining the digital twin of the physical system. The book also presents novel, data-driven algorithms to handle non- Euclidean data. In summary, this book presents a novel perspective for modeling the CPS.

Network Embedded Management and Applications

Author : Alexander Clemm
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Despite the explosion of networking services and applications in the past decades, the basic technological underpinnings of the Internet have remained largely unchanged. At its heart are special-purpose appliances that connect us to the digital world, commonly known as switches and routers. Now, however, the traditional framework is being increasingly challenged by new methods that are jostling for a position in the “next-generation” Internet. The concept of a network that is becoming more programmable is one of the aspects that are taking center stage. This opens new possibilities to embed software applications inside the network itself and to manage networks and communications services with unprecedented ease and efficiency. In this edited volume, distinguished experts take the reader on a tour of different facets of programmable network infrastructure and applications that exploit it. Presenting the state of the art in network embedded management and applications and programmable network infrastructure, the book conveys fundamental concepts and provides a glimpse into various facets of the latest technology in the field.

The Semantic Web ISWC 2017

Author : Claudia d'Amato
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The two-volume set LNCS 10587 + 10588 constitutes the refereed proceedings of the 16th International Semantic Web Conference, ISWC 2017, held in Vienna, Austria, in October 2017. ISWC 2017 is the premier international forum, for the Semantic Web / Linked Data Community. The total of 55 full and 21 short papers presented in this volume were carefully reviewed and selected from 300 submissions. They are organized according to the tracks that were held: Research Track; Resource Track; and In-Use Track.

Vehicular Social Networks

Author : Anna Maria Vegni
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The book provides a comprehensive guide to vehicular social networks. The book focuses on a new class of mobile ad hoc networks that exploits social aspects applied to vehicular environments. Selected topics are related to social networking techniques, social-based routing techniques applied to vehicular networks, data dissemination in VSNs, architectures for VSNs, and novel trends and challenges in VSNs. It provides significant technical and practical insights in different aspects from a basic background on social networking, the inter-related technologies and applications to vehicular ad-hoc networks, the technical challenges, implementation and future trends.