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An approach to identify candidate services for semantic web service discovery

机译:一种识别候选服务以进行语义Web服务发现的方法

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A two-stage filtering approach based on implicit semantics of web service description and WordNet is proposed to identify candidate services during semantic service discovery using semantic reasoners. In the first stage, the candidate services relevant to the given service query are identified after filtering out irrelevant services. In the second stage, the trust score of each candidate service is compared against a user-defined trust score using Trust Rank algorithmic tool. Only those candidate services with trust score greater than the user-defined trust score are considered as the services which necessarily require complete semantic matching of service capabilities using a semantic reasoner. The proposed approach has been evaluated for accuracy using recall and precision. The results are compared with keyword based matching. With a typical test data of 90 services, the proposed method has average recall of 88.2% and average precision of 63.7% in contrast to keyword based matching which has average recall of 64.8% and average precision of 36.7%. Further, the proposed method has an average reduction of number of services of 97.3% and achieves optimization at matching level significantly.
机译:提出了一种基于Web服务描述和Wordnet隐式语义的两阶段过滤方法,以识别使用语义推理员在语义服务发现期间识别候选服务。在第一阶段,在过滤无关的服务后识别与给定服务查询相关的候选服务。在第二阶段,将每个候选服务的信任分数与使用信任秩算法工具的用户定义的信任分数进行比较。只有与用户定义的信任分数大于用户定义的信任分数的那些候选服务被视为必然需要使用语义推理的服务能力完全语义匹配。已经使用召回和精度评估了所提出的方法。将结果与基于关键字的匹配进行比较。通过90种服务的典型测试数据,该方法的平均召回量为88.2%,平均精度为63.7%,与基于关键词的匹配相比,平均召回为64.8%,平均精度为36.7%。此外,所提出的方法平均降低了97.3%的服务数量,并显着实现了匹配水平的优化。

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