Feedback

X
Hypergraph Computation

Hypergraph Computation

and

en

0 Ungluers have Faved this Work
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.

This book is included in DOAB.

Why read this book? Have your say.

You must be logged in to comment.

Rights Information

Are you the author or publisher of this work? If so, you can claim it as yours by registering as an Unglue.it rights holder.

Downloads

This work has been downloaded 27 times via unglue.it ebook links.
  1. 27 - pdf (CC BY) at Unglue.it.

Keywords

  • Algorithms & data structures
  • artificial intelligence
  • Complex Correlation Modelling
  • Computer programming / software development
  • Computer science
  • Computing & information technology
  • High-Order Correlation Modelling
  • hypergraph
  • Hypergraph Computation
  • hypergraph learning
  • Hypergraph Modelling
  • Hypergraph Neural Network
  • 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

Links

DOI: 10.1007/978-981-99-0185-2

Editions

edition cover

Share

Copy/paste this into your site: