With an increasing number of Geographical Information System (GIS) services publicly available on the Web, the discovery of composite GIS services is promising when novel requirements are to be satisfied. GIS services in the repository like ArcGIS software are organized in a tree hierarchy, where a parent node represents a categorial GIS service with a coarser-granularity than its child GIS services, while leaf nodes correspond to atomic and exercisable GIS services. In this setting, discovering appropriate atomic GIS services is challenging. To remedy this issue, this paper proposes a composite GIS service discovery mechanism. Specifically, for the given requirement, select the parent nodes that take the given input parameters as input and remove their inactivated children. Use remaining children to build the network and repeat the previous operation until finding the services that contain the required output. Then record the semantic similarity degree, calculated by services functional description, in this network. By using the simulated annealing algorithm, a composite GIS services solution will be recommended from this semantic network. Evaluation results demonstrate that our approach could give more significant solution compared with the state-of-the-art techniques.

中文翻译：

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组合 GIS 服务的语义发现

随着越来越多的地理信息系统 (GIS) 服务在 Web 上公开可用，当要满足新的需求时，复合 GIS 服务的发现是有希望的。知识库中的 GIS 服务（如 ArcGIS 软件）以树状层次结构组织，其中父节点表示分类的GIS 服务较粗-粒度比其子 GIS 服务，而叶子节点对应原子和可行使地理信息系统服务。在这种情况下，发现合适的原子 GIS 服务具有挑战性。为了解决这个问题，本文提出了一种复合式GIS服务发现机制。具体来说，对于给定的需求，选择以给定的输入参数作为输入的父节点，并移除其未激活的子节点。使用剩余的孩子构建网络并重复前面的操作，直到找到包含所需输出的服务。然后记录该网络中通过服务功能描述计算的语义相似度。通过使用模拟退火算法，从这个语义网络中推荐一个复合的 GIS 服务解决方案。评估结果表明，与最先进的技术相比，我们的方法可以提供更重要的解决方案。