358 research outputs found
Krausz dimension and its generalizations in special graph classes
A {\it krausz -partition} of a graph is the partition of into
cliques, such that any vertex belongs to at most cliques and any two
cliques have at most vertices in common. The {\it -krausz} dimension
of the graph is the minimum number such that has a
krausz -partition. 1-krausz dimension is known and studied krausz
dimension of graph .
In this paper we prove, that the problem is polynomially
solvable for chordal graphs, thus partially solving the problem of P. Hlineny
and J. Kratochvil. We show, that the problem of finding -krausz dimension is
NP-hard for every , even if restricted to (1,2)-colorable graphs, but
the problem is polynomially solvable for -polar
graphs for every fixed
Anomaly Detection on Graph Time Series
In this paper, we use variational recurrent neural network to investigate the
anomaly detection problem on graph time series. The temporal correlation is
modeled by the combination of recurrent neural network (RNN) and variational
inference (VI), while the spatial information is captured by the graph
convolutional network. In order to incorporate external factors, we use feature
extractor to augment the transition of latent variables, which can learn the
influence of external factors. With the target function as accumulative ELBO,
it is easy to extend this model to on-line method. The experimental study on
traffic flow data shows the detection capability of the proposed method
Ontologies on the semantic web
As an informational technology, the World Wide Web has enjoyed spectacular success. In just ten years it has transformed the way information is produced, stored, and shared in arenas as diverse as shopping, family photo albums, and high-level academic research. The “Semantic Web” was touted by its developers as equally revolutionary but has not yet achieved anything like the Web’s exponential uptake. This 17 000 word survey article explores why this might be so, from a perspective that bridges both philosophy and IT
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