Titlebook: Discovery Science; 16th International C Johannes Fürnkranz,Eyke Hüllermeier,Tomoyuki Higuc Conference proceedings 2013 Springer-Verlag Berl

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reperfusion

Johannes Fürnkranz,Eyke Hüllermeier,Tomoyuki HigucConference proceedings of the International Conference on Discovery Science, DS 2013

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https://doi.org/10.1007/978-3-642-40897-7constraint-based clustering; domain ontology; hypernetworks; semantic data mining; structure learning; al

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自然环境

Fast Compression of Large-Scale Hypergraphs for Solving Combinatorial Problems,ses multikey Quicksort given by Bentley and Sedgewick. By conducting experiments with various datasets, we show that our algorithm is significantly faster and requires much smaller memory than an existing method.

Hallowed

Mining Interesting Patterns in Multi-relational Data with N-ary Relationships,ps were restricted to be binary, as well as of prior work on local pattern mining from a single .-ary relationship. Remarkably, despite being more general our algorithm is comparably fast or faster than the state-of-the-art in these less general problem settings.

停止偿付

Inductive Process Modeling of Rab5-Rab7 Conversion in Endocytosis,st introduce a formal representation of the domain knowledge for modeling this process. We then present the design of the IPM experiments using the domain knowledge and measured data and the results obtained from these experiments. We finally compare our results with results already published in the literature.

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