BiQL: a query language for analyzing information networks
Bisociative Knowledge Discovery
Review of bisonet abstraction techniques
Bisociative Knowledge Discovery
Simplification of networks by edge pruning
Bisociative Knowledge Discovery
Finding representative nodes in probabilistic graphs
Bisociative Knowledge Discovery
Node similarities from spreading activation
Bisociative Knowledge Discovery
Towards discovery of subgraph bisociations
Bisociative Knowledge Discovery
Towards bisociative knowledge discovery
Bisociative Knowledge Discovery
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Heterogeneous information networks or BisoNets, as they are called in the context of bisociative knowledge discovery, are a flexible and popular form of representing data in numerous fields. Additionally, such networks can be created or derived from other types of information using, e.g., the methods given in Part II of this volume. This part of the book describes various network algorithms for the exploration and analysis of BisoNets. Their general goal is to support and partially even automate the process of bisociation. More specific goals are to allow navigation of BisoNets by indirect and predicted relationships and by analogy, to produce explanations for discovered relationships, and to help abstract and summarise BisoNets for more effective visualisation.