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It is also more challenging than graph pattern mining since it has to deal with disconnected patterns (see (varphi _1) of Example 5) and forbidding (mathsf {GFDs}) that do not expect to find matches in any consistent graphs (e.g., (varphi _3)), not to mention their intractable satisfiability and implication analyses.
In addition, we frequently treat consistent graphs as sets of nodes or functional terms and use set operations to manipulate them.
Note that this type of analysis is related to the theory on monotone systems and the notion of consistent graphs [ 24, 22].
Operations between consistent graphs (labelings) result in consistent graphs (labelings) as well, because the edge set of the last is the union or the intersection of the operands and therefore a particular edge has to pre-exist in at least one of the operands without violating the TPR.
Semantic distance between two consistent graphs P and T is defined as S k (P, T ) = (r u k (P, T ) + m i k (P, T ) ) 1 k for any k ≥ 1.
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In this method, the relationship between camera poses is represented as a graph and the consistent graph is built to suppress the error in the optimization.
An interesting anomaly with this approach is that the marginal probability, and subsequently the information content, of a single term (i.e. consistent graph with a single leaf term) calculated from a Bayesian network does not necessarily match the relative term frequency in the database (instead, the conditional probability tables are estimated as relative frequencies).
The population is first initialized with consistent labelings (graphs) and evolved exploiting the graph-union and graph-intersection operations between individuals.
From these toy examples it is easy to see that the reconciled marginal distributions correspond to internally consistent pathway graphs.
That may not be especially surprising, but it's interesting to see just how consistent the graph below is.
Our measurement of mitochondria degradation at 24, 48 and 72 h post transfection was also consistent (see graph in Figure 4e).
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