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A neural model for semantically enhancing Web APIs

机译：语义增强Web API的神经模型

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The paper describes an unsupervised neural model for classifying the methods of Web APIs into a large number of classes specified by a domain ontology. As a result of the classification, each method of a Web service is associated to one ontology concept, the name of the concept being further used to semantically annotate the method. The ontology concepts define some functionalities to be offered by different API methods. The names of these concepts are linguistically denoted by verbs or verb phrases that define the action performed by a method. The framework is based on a model of hierarchical self-organizing maps. The methods of the web APIs are encoded in a bag-of-words style, by counting the words that occur in their javadoc documentation. We experimented this automatic semantic annotation model with a data set consisting of APIs of RDF storage tools. The ontology and the APIs to be classified in our experiments are collected from this dataset.
机译：本文介绍了一种无监督的神经模型，用于将Web API的方法分类为域本体指定的大量类别。由于分类，Web服务的每个方法与一个本体概念相关联，该概念的名称进一步用于语义上注释该方法。本体概念定义了不同API方法提供的一些功能。这些概念的名称是由动词或动词短语来语言语，定义方法执行的操作。该框架基于分层自组织地图的模型。通过计算在其Javadoc文档中发生的单词，Web API的方法以文字袋式进行编码。我们尝试了具有由RDF存储工具的API组成的数据集的自动语义注释模型。在我们的实验中分类的本体和API是从这个数据集收集的。

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