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Author: Qionghai Dai
Publisher: Springer Nature
ISBN: 9819901855
Category : Computers
Languages : en
Pages : 251
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Book Description
This open access book discusses the theory and methods of hypergraph computation. Many underlying relationships among data can be represented using graphs, for example in the areas including computer vision, molecular chemistry, molecular biology, etc. In the last decade, methods like graph-based learning and neural network methods have been developed to process such data, they are particularly suitable for handling relational learning tasks. In many real-world problems, however, relationships among the objects of our interest are more complex than pair-wise. Naively squeezing the complex relationships into pairwise ones will inevitably lead to loss of information which can be expected valuable for learning tasks. Hypergraph, as a generation of graph, has shown superior performance on modelling complex correlations compared with graph. Recent years have witnessed a great popularity of researches on hypergraph-related AI methods, which have been used in computer vision, social media analysis, etc. We summarize these attempts as a new computing paradigm, called hypergraph computation, which is to formulate the high-order correlations underneath the data using hypergraph, and then conduct semantic computing on the hypergraph for different applications. The content of this book consists of hypergraph computation paradigms, hypergraph modelling, hypergraph structure evolution, hypergraph neural networks, and applications of hypergraph computation in different fields. We further summarize recent achievements and future directions on hypergraph computation in this book.
Author: Qionghai Dai
Publisher: Springer Nature
ISBN: 9819901855
Category : Computers
Languages : en
Pages : 251
Get Book Here
Book Description
This open access book discusses the theory and methods of hypergraph computation. Many underlying relationships among data can be represented using graphs, for example in the areas including computer vision, molecular chemistry, molecular biology, etc. In the last decade, methods like graph-based learning and neural network methods have been developed to process such data, they are particularly suitable for handling relational learning tasks. In many real-world problems, however, relationships among the objects of our interest are more complex than pair-wise. Naively squeezing the complex relationships into pairwise ones will inevitably lead to loss of information which can be expected valuable for learning tasks. Hypergraph, as a generation of graph, has shown superior performance on modelling complex correlations compared with graph. Recent years have witnessed a great popularity of researches on hypergraph-related AI methods, which have been used in computer vision, social media analysis, etc. We summarize these attempts as a new computing paradigm, called hypergraph computation, which is to formulate the high-order correlations underneath the data using hypergraph, and then conduct semantic computing on the hypergraph for different applications. The content of this book consists of hypergraph computation paradigms, hypergraph modelling, hypergraph structure evolution, hypergraph neural networks, and applications of hypergraph computation in different fields. We further summarize recent achievements and future directions on hypergraph computation in this book.
Author: Marius George Linguraru
Publisher: Springer Nature
ISBN: 3031720865
Category :
Languages : en
Pages : 815
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Book Description
Author: Alain Bretto
Publisher: Springer Science & Business Media
ISBN: 3319000802
Category : Mathematics
Languages : en
Pages : 129
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Book Description
This book provides an introduction to hypergraphs, its aim being to overcome the lack of recent manuscripts on this theory. In the literature hypergraphs have many other names such as set systems and families of sets. This work presents the theory of hypergraphs in its most original aspects, while also introducing and assessing the latest concepts on hypergraphs. The variety of topics, their originality and novelty are intended to help readers better understand the hypergraphs in all their diversity in order to perceive their value and power as mathematical tools. This book will be a great asset to upper-level undergraduate and graduate students in computer science and mathematics. It has been the subject of an annual Master's course for many years, making it also ideally suited to Master's students in computer science, mathematics, bioinformatics, engineering, chemistry, and many other fields. It will also benefit scientists, engineers and anyone else who wants to understand hypergraphs theory.
Author: Ika Hesti Agustin
Publisher: Springer Nature
ISBN: 9464634456
Category : Electronic books
Languages : en
Pages : 281
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Book Description
Author: Fabian Kuhn
Publisher: Springer
ISBN: 3662451743
Category : Computers
Languages : en
Pages : 594
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Book Description
This book constitutes the proceedings of the 28th International Symposium on Distributed Computing, DISC 2014, held in Austin, TX, USA, in October 2014. The 35 full papers presented in this volume were carefully reviewed and selected from 148 full paper submissions. In the back matter of the volume a total of 18 brief announcements is presented. The papers are organized in topical sections named: concurrency; biological and chemical networks; agreement problems; robot coordination and scheduling; graph distances and routing; radio networks; shared memory; dynamic and social networks; relativistic systems; transactional memory and concurrent data structures; distributed graph algorithms; and communication.
Author: Victor Malyshkin
Publisher: Springer
ISBN: 3642231780
Category : Computers
Languages : en
Pages : 512
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Book Description
This book constitutes the proceedings of the 11th International Conference on Parallel Computing Technologies, PaCT 2011, held in Kazan, Russia on September 19-23, 2011. The 44 full papers presented together with 2 invited papers were carefully reviewed and selected from 68 submissions. The papers are organized in topical sections on models and languages, cellular automata, parallel programming tools and support, and applications.
Author: Manish Parashar
Publisher: John Wiley & Sons
ISBN: 0470558016
Category : Computers
Languages : en
Pages : 542
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Book Description
A unique investigation of the state of the art in design, architectures, and implementations of advanced computational infrastructures and the applications they support Emerging large-scale adaptive scientific and engineering applications are requiring an increasing amount of computing and storage resources to provide new insights into complex systems. Due to their runtime adaptivity, these applications exhibit complicated behaviors that are highly dynamic, heterogeneous, and unpredictable—and therefore require full-fledged computational infrastructure support for problem solving, runtime management, and dynamic partitioning/balancing. This book presents a comprehensive study of the design, architecture, and implementation of advanced computational infrastructures as well as the adaptive applications developed and deployed using these infrastructures from different perspectives, including system architects, software engineers, computational scientists, and application scientists. Providing insights into recent research efforts and projects, the authors include descriptions and experiences pertaining to the realistic modeling of adaptive applications on parallel and distributed systems. The first part of the book focuses on high-performance adaptive scientific applications and includes chapters that describe high-impact, real-world application scenarios in order to motivate the need for advanced computational engines as well as to outline their requirements. The second part identifies popular and widely used adaptive computational infrastructures. The third part focuses on the more specific partitioning and runtime management schemes underlying these computational toolkits. Presents representative problem-solving environments and infrastructures, runtime management strategies, partitioning and decomposition methods, and adaptive and dynamic applications Provides a unique collection of selected solutions and infrastructures that have significant impact with sufficient introductory materials Includes descriptions and experiences pertaining to the realistic modeling of adaptive applications on parallel and distributed systems The cross-disciplinary approach of this reference delivers a comprehensive discussion of the requirements, design challenges, underlying design philosophies, architectures, and implementation/deployment details of advanced computational infrastructures. It makes it a valuable resource for advanced courses in computational science and software/systems engineering for senior undergraduate and graduate students, as well as for computational and computer scientists, software developers, and other industry professionals.
Author: Robert Stahlbock
Publisher: Springer Nature
ISBN: 3030717046
Category : Computers
Languages : en
Pages : 965
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Book Description
The book presents the proceedings of two conferences: the 16th International Conference on Data Science (ICDATA 2020) and the 19th International Conference on Information & Knowledge Engineering (IKE 2020), which took place in Las Vegas, NV, USA, July 27-30, 2020. The conferences are part of the larger 2020 World Congress in Computer Science, Computer Engineering, & Applied Computing (CSCE'20), which features 20 major tracks. Papers cover all aspects of Data Science, Data Mining, Machine Learning, Artificial and Computational Intelligence (ICDATA) and Information Retrieval Systems, Information & Knowledge Engineering, Management and Cyber-Learning (IKE). Authors include academics, researchers, professionals, and students. Presents the proceedings of the 16th International Conference on Data Science (ICDATA 2020) and the 19th International Conference on Information & Knowledge Engineering (IKE 2020); Includes papers on topics from data mining to machine learning to informational retrieval systems; Authors include academics, researchers, professionals and students.
Author: Jie Shao
Publisher: Springer
ISBN: 3030260720
Category : Computers
Languages : en
Pages : 446
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Book Description
This two-volume set, LNCS 11641 and 11642, constitutes the thoroughly refereed proceedings of the Third International Joint Conference, APWeb-WAIM 2019, held in Chengdu, China, in August 2019. The 42 full papers presented together with 17 short papers, and 6 demonstration papers were carefully reviewed and selected from 180 submissions. The papers are organized around the following topics: Big Data Analytics; Data and Information Quality; Data Mining and Application; Graph Data and Social Networks; Information Extraction and Retrieval; Knowledge Graph; Machine Learning; Recommender Systems; Storage, Indexing and Physical Database Design; Spatial, Temporal and Multimedia Databases; Text Analysis and Mining; and Demo.
Author: Sergio Flesca
Publisher: Springer
ISBN: 3540457577
Category : Computers
Languages : en
Pages : 589
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Book Description
This book constitutes the refereed proceedings of the European Conference on Logics in Artificial Intelligence, JELIA 2002, held in Cosenza, Italy in September 2002.The 41 revised full papers presented together with 11 system descriptions and 3 invited contributions were carefuly reviewed and selected from more than 100 submissions. The papers are organized in topical sections on multi-agent systems, evolution and changes, description logic and the semantic web, complexity issues, probabilistic logic, AI planning, modal logic and causal reasoning, theory, reasoning under uncertainty, satisfiability, paraconsisten reasoning, actions and caution, logic for agents, semantics, and optimization issues in answer set semantics.
