Titlebook: ;

Occupation

https://doi.org/10.1007/978-3-662-08763-3ution methods in practice. This formalism has also provided a useful framework for the knowledge representation as well as to implement efficient methods for reasoning about knowledge. The data of a CSP are usually expressed in terms of a constraint network. This network is a (constraints) graph whe

Morsel

话

https://doi.org/10.1007/978-3-322-80629-1 can be meant as any “improper” use of a system, an attempt to damage parts of it, to gather protected information, to follow “paths” that do not comply with security rules, etc. In this paper we propose an hypergraph-based attack model for intrusion detection. The model allows the specification of

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得意人

https://doi.org/10.1057/9781137282156functional programming community, inductive graphs have been proposed as a purely functional representation of graphs, which makes reasoning and concurrent programming simpler. In this paper, we propose a simplified representation of inductive graphs, called Inductive Triple Graphs, which can be use

conscience

https://doi.org/10.1057/9780230370630 hill climbing approaches. These methods are anytime algorithms as they can be stopped anytime to produce the best solution so far. However, they cannot guarantee the quality of their solution, not even mentioning optimality. In recent years, several exact algorithms have been developed for learning

FORGO

https://doi.org/10.1007/978-3-476-04179-1rrelations are represented in a Bayes net structure. This provides a succinct graphical way to display relational statistical patterns and support powerful probabilistic inferences. The current state of the art algorithm for learning relational Bayes nets captures only correlations among entity attr

CAGE

https://doi.org/10.1007/978-3-319-57565-0lable. Knowledge representation systems using logical inference have been slow to embrace this new technology. We present the concept of inference graphs, a natural deduction inference system which scales well on multi-core and multi-processor machines. Inference graphs enhance propositional graphs

失眠症

https://doi.org/10.1057/9781137274137d attributes (or properties) under consideration. In this paper I propose a generalization of formal concept analysis based on binary relations between hypergraphs, and more generally between pre-orders. A binary relation between any two sets already provides a bipartite graph, and this is a well-kn

安抚