一种指导用户发现服务的概念分析方法

Bipin Upadhyaya, Foutse Khomh, Ying Zou, Alex Lau, J. Ng
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引用次数: 9

摘要

Web服务被广泛用作构建速度快、成本低的复杂分布式应用程序的基本结构。然而,现有的服务发现技术为用户提供的结果很差,需要大量的人工干预来过滤服务以定位所需的服务。特别是,用户通常事先不知道Web上可用服务的功能描述。用户制定的查询可能与现有服务的服务描述不太匹配。因此,用户的查询可能导致大量返回的服务。本文提出了一种从服务描述中提取语义概念的方法,并在此基础上对服务进行聚类。因此,每个概念都与一组相关服务相关联。为了理解用户查询的语义含义,我们识别查询背后的概念,并推荐与服务相关的相关概念。我们的方法还指导用户制定他们的查询。我们进行了一个案例研究,发现我们的服务发现方法的平均准确率和召回率分别为83%和100%。我们还执行了一项用户研究,该研究表明,在85%的情况下,用户使用我们的方法提供的建议来重新制定查询,以提高检索服务的精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A concept analysis approach for guiding users in service discovery
Web services are widely used as basic constructs to build complex distributed applications with fast speed and low cost. However, existing service discovery techniques provide users with poor results which require substantial human intervention to filter the services to locate the desired ones. In particular, users often have no prior knowledge of the functional description of the available services on the Web. The queries formulated by the users may not match well with the service descriptions of existing services. As a consequence, a user's query can result in a large number of returned services. In this paper, we propose an approach that derives the semantic concepts conveyed in the service descriptions and clusters the services based on the concepts. As a result, each concept is associated with a set of relevant services. To understand the semantic meanings of a user's query, we identify concepts behind the query and recommend related concepts associated with services. Our approach also guides users to formulate their queries. We conducted a case study and found that the average precision and recall of our approach for service discovery are respectively, 83% and 100%. We also performed a user study which shows that for 85% of time, a user reformulates their queries using the suggestion provided by our approach to improve the precision of the retrieved services.
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