中文摘要：

社会化标注已经成为当前Web2.0时代流行的资源识别和管理方法.针对当前Web服务语义描述能力不足的问题,提出一种基于多维度的Web服务语义社会标注方法.在社会标注模型的指导下,利用涉众的广泛参与性,从推荐标签集、候选标签集以及自由标签集3种集合中选取若干个标签对服务进行社会标注;同时从服务的功能语义、非功能语义、目标语义、交互语义和补充语义5个维度建立服务语义社会标注框架,给出具体标注类型,将其分为机器标注和群体标注,利用群体智能,对机器标注的服务语义进行修正和完善,提高Web服务语义描述的完整性（即服务标签的语义覆盖率）.进而作者提出了一种服务语义自动浮现方法,结合服务语义维度优先级,并根据标签出现频率以及服务属性类型优先级对标签进行排序,使得Web服务能够呈现大众用户认可的语义信息,提高Web服务语义描述的准确性（即服务标签的有效使用率）,为后期准确发现Web服务奠定基础.最后通过实验分析,验证上述方法在提高服务语义描述能力方面的实用性和有效性.

英文摘要：

Social tagging has become a popular solution for recognition and management of resources in Web2.0 era.To solve the current problem of insufficient capacity of semantic description of Web services,a multi-dimensional social tagging approach for Web services semantics is proposed.Under the guidance of social tagging model,users can choose several tags to annotate services from the three sets of recommendation set,candidate set and free set;simultaneously,social tagging framework of service semantics is established from five dimensions of functional semantics,non functional semantics,objective semantics,interactive semantics and complementary semantics,and specific tagging types given,which are divided into machine＇s annotation and human＇s annotation,with the support of collective intelligence,machine＇s tags can be modified and perfected so that the semantic coverage rate of Web service can be enhanced;Moreover,an approach of service semantics emerges automatically is proposed in this paper,through setting the priority of service semantics dimensions,according to frequency to sort the social tags,so that Web services can show semantic information which the public users approve,and which lays the foundation for later discovering the Web services accurately.Finally,experimental results verify the feasibility and effectiveness of this approach.