基于Folksonomy的服务发现研究

Study on Folksonomy-based webservice discovery

为解决UDDI中传统分类系统分类粒度过、维护困难等问题,提出了一种基于Folksonomy的Web服务发现模型,并对模型的具体实现方案进行了详细探讨。分析了Folksonomy机制本身的缺陷,并利用维基百科和WordNet进行了一系列改进。利用程序模拟了协作标签系统环境,并进行了模拟实验。实验结果表明,该机制能实现更为高效的Web服务分类检索,针对Folksonomy改进措施对提高查全率和查准率具有积极作用。

To solve traditional classification system＇s problems of coarse-grain classification and high costmaintenance,a Folksonomybased web service discovery model is proposed and its concrete realization method is deeply analyzed.The disadvantages of Folksonomy mechanism are analyzed,and a series of measures are taken according to that.The collaborative tagging system environment is simulated by programming,and a simulation experiment is conducted in it.Experimental results prove that the mechanism can realize more efficient web service classification retrieval,and the improvements applied to Folksonomy have positive impacts on both recall ratio and precision ratio.