The SDMLib Solution to the Class Responsibility Assignment Case for TTC2016
The SDMLib Solution to the Class Responsibility Assignment Case for TTC2016
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TTC2016 班级责任分配案例的 SDMLib 解决方案
DOI：
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发表时间：
2016
期刊：
影响因子：
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通讯作者：
Albert Zündorf
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作者：
C. Eickhoff;Lennert Raesch;Albert Zündorf
c Albert Zündorf 本作品根据知识共享署名许可获得许可。本文介绍了 SDMLib 对 TTC2016 班级责任分配案例的解决方案。 SDMLib 提供了 Groove 的可达性图计算。因此，简单的想法是为可能的聚类操作提供规则，然后使用可达性图计算来生成所有可能的聚类。然后，我们将 CRAIndex 计算应用于每个生成的聚类并识别最佳聚类。当然，这很快就会遇到可扩展性问题。因此，我们扩展了可达性图计算来进行基于 A* 的搜索空间探索。因此，我们将 CRAIndex 计算作为可达性图计算的指标，并且在每一步中，我们都会考虑一组尚未扩展的图，并选择具有最佳扩展指标值的图。该论文报告了我们通过这种方法取得的成果。
c Albert Zündorf This work is licensed under the Creative Commons Attribution License. This paper describes the SDMLib solution to the Class Responsibility Assignment Case for TTC2016. SDMLib provides reachability graph computation ala Groove. Thus, the simple idea was to provide rules for possible clustering operations and then use the reachability graph computation to generate all possible clusterings. Then, we apply the CRAIndex computation to each generated clustering and identify the best clustering. Of course, this runs into scalability problems, very soon. Thus, we extended our reachability graph computation to do an A* based search space exploration. Therefore, we passed the CRAIndex computation as a metric to our reachability graph computation and in each step, we consider the set of not yet expanded graphs and choose the one, that has the best metric value for expansion. The paper reports about the results we achieved with this approach.