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Label algorithm was the first approach to use social characteristics in opportunistic networks.
This is because embedded within the label "algorithm" is a notion of context and substrate-independence.
If not, we may again use the double label algorithm computing exact results in polynomial time.
If a single label algorithm is used, the multiple labels are usually divided and then calculated.
In acyclic graphs, we can again use the double label algorithm adapted for MAX-metric.
We may employ the double label algorithm, a generalized version of the Dijkstra algorithm for computing shortest positive/negative paths in Σ-metric.
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On the other hand, label algorithms, such as box plots, assign a label (normal or outlier) to each evidence.
Therefore it is highly desirable to design and implement a new efficient SVM-type multi-label algorithm.
Therefore it is highly desirable to design and implement a novel efficient SVM-type multi-label algorithm.
Hybrid strategy, which generalizes a specific single-label algorithm while one or two data decomposition tricks are applied implicitly or explicitly, has become an effective and efficient tool to design and implement various multi-label classification algorithms.
In this paper, we extend the prime number schema labelling algorithm for labelling DAG XML graph.
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