Hypergraph Computation
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 le...
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| Materyal Türü: | Online |
| Dil: | İngilizce |
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Springer Nature
2023
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| Konular: | |
| Online Erişim: | ONIX_20230620_9789819901852_49 |
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| _version_ | 1869522948627365888 |
|---|---|
| author | Dai, Qionghai Gao, Yue |
| author_browse | Dai, Qionghai Gao, Yue |
| author_facet | Dai, Qionghai Gao, Yue |
| author_sort | Dai, Qionghai |
| collection | Directory of Open Access Books |
| 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. |
| format | Online |
| id | doab-20.500.12854ir-101674 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2023 |
| publishDateRange | 2023 |
| publishDateSort | 2023 |
| publisher | Springer Nature |
| publisherStr | Springer Nature |
| record_format | ojs |
| spelling | doab-20.500.12854ir-1016742025-07-17T10:01:15Z Hypergraph Computation Dai, Qionghai Gao, Yue Hypergraph Hypergraph Computation Hypergraph Learning Hypergraph Modelling Hypergraph Neural Network Complex Correlation Modelling High-Order Correlation Modelling thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQM Machine learning thema EDItEUR::U Computing and Information Technology::UM Computer programming / software engineering::UMB Algorithms and data structures thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQM Machine learning thema EDItEUR::U Computing and Information Technology::UM Computer programming / software engineering::UMB Algorithms and data structures 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. 2023-07-19T09:24:46Z 2023-07-19T09:24:46Z 2023-06-20T10:31:03Z 2023 book ONIX_20230620_9789819901852_49 https://library.oapen.org/handle/20.500.12657/63610 9789819901852 9789819901845 https://directory.doabooks.org/handle/20.500.12854/101674 eng Artificial Intelligence: Foundations, Theory, and Algorithms open access image/jpeg image/jpeg n/a n/a https://library.oapen.org/bitstream/20.500.12657/63610/1/978-981-99-0185-2.pdf https://library.oapen.org/bitstream/20.500.12657/63610/1/978-981-99-0185-2.pdf Springer Nature Springer Nature Singapore 10.1007/978-981-99-0185-2 10.1007/978-981-99-0185-2 9fa3421d-f917-4153-b9ab-fc337c396b5a Tsinghua University e06840e4-106f-423f-bba7-d034dee9cf25 9789819901852 9789819901845 Springer Nature Singapore 244 Singapore [...] open access |
| spellingShingle | Hypergraph Hypergraph Computation Hypergraph Learning Hypergraph Modelling Hypergraph Neural Network Complex Correlation Modelling High-Order Correlation Modelling thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQM Machine learning thema EDItEUR::U Computing and Information Technology::UM Computer programming / software engineering::UMB Algorithms and data structures thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQM Machine learning thema EDItEUR::U Computing and Information Technology::UM Computer programming / software engineering::UMB Algorithms and data structures Dai, Qionghai Gao, Yue Hypergraph Computation |
| title | Hypergraph Computation |
| title_full | Hypergraph Computation |
| title_fullStr | Hypergraph Computation |
| title_full_unstemmed | Hypergraph Computation |
| title_short | Hypergraph Computation |
| title_sort | hypergraph computation |
| topic | Hypergraph Hypergraph Computation Hypergraph Learning Hypergraph Modelling Hypergraph Neural Network Complex Correlation Modelling High-Order Correlation Modelling thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQM Machine learning thema EDItEUR::U Computing and Information Technology::UM Computer programming / software engineering::UMB Algorithms and data structures thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQM Machine learning thema EDItEUR::U Computing and Information Technology::UM Computer programming / software engineering::UMB Algorithms and data structures |
| topic_facet | Hypergraph Hypergraph Computation Hypergraph Learning Hypergraph Modelling Hypergraph Neural Network Complex Correlation Modelling High-Order Correlation Modelling thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQM Machine learning thema EDItEUR::U Computing and Information Technology::UM Computer programming / software engineering::UMB Algorithms and data structures thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQM Machine learning thema EDItEUR::U Computing and Information Technology::UM Computer programming / software engineering::UMB Algorithms and data structures |
| url | ONIX_20230620_9789819901852_49 |
| work_keys_str_mv | AT daiqionghai hypergraphcomputation AT gaoyue hypergraphcomputation |