Semantic Web service discovery based on WordNet ontology and PLSA
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摘要: 提出了一种基于WordNet本体标注和概率潜在语义分析(PLSA,Probabilistic Latent Semantic Analysis)的语义Web服务发现方法OntoPLSA.首先使用WordNet本体标注Web服务的操作名、参数以及用户请求,以经过标注后的输出参数集合为词汇集,服务描述文档集合为文档集,组成词汇-文档矩阵,以该矩阵为输入,使用PLSA方法对服务集进行分类,并将用户请求带入PLSA模型,确定其所属的类;然后在类中以标注后的输出参数为键,含有这个输出的服务的列表为键值,建立一个映射表,查找与用户请求的输出相似的映射表键,进而找出对应的键值,即服务列表;最后根据QoS(Quality of Service)和用户请求中的输入参数确定满足条件的服务结果集合.在415个Web服务组成的数据集上的测试结果表明,性能较其他方法有优势,召回率和R准确率也得到了改善.Abstract: A semantic Web service discovery based on WordNet ontology and PLSA (Probabilistic Latent Semantic Analysis) was proposed. Firstly, the operation name, input parameters, output parameters and the query request were annotated by WordNet ontology. Then the annotated output parameters were taken as term set, and web services as document set to construct a vocabulary-document matrix. After that the query request was taken as service and was injected into the PLSA model to determine its category. Secondly, in this category, a mapping table was established. The output parameters of services were taken as map key, and services list which contained the output parameter was taken as the key value for the map. Each output parameter of query request could match the map keys which were similar to themselves. According to the matched map key, the corresponding list of services would be identified, and then the service set that was compatible with QoS requirements also would be identified. Finally, the final service result set would be acquired according to the query request input parameters. Testing data set including 415 web services was used to make an experiment for this method. Results show that not only the performance is better than other methods but also R-precision and recall rate have been improved.
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Key words:
- ontology annotation /
- probabilistic latent semantic analysis /
- Web service /
- indexing /
- classification /
- semantics /
- service discovery
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