为了提高在多种来源之间发现特定服务的效率,结合信息检索技术提出了针对多源Web服务的服务发现方法,有效地克服了不同Web服务发布方式之间服务发现的障碍,综合管理多种Web服务描述及其语义信息,提供了基于语义的服务查询。在分析相关研究不足基础上给出了服务发现框架MWSD(multi-source Web service discovery),并介绍了框架中各模块的作用,说明了不同服务描述之间的映射关系。结果表明:MWSD能够自动获取不同来源,不同描述的Web服务信息,并利用不同描述之间的映射关系建立统一的Web服务资源库,管理Web服务的复杂语义,可用于互联网上开放的Web服务发现。
This paper presents a cross-media semantic mining model （CSMM） based on object semantic. This model obtains object-level semantic information in terms of maximum probability principle. Then semantic templates are trained and constructed with STTS （Semantic Template Training System）, which are taken as the bridge to realize the transition from various low-level media feature to object semantic. Furthermore, we put forward a kind of double layers metadata structure to efficaciously store and manage mined low-level feature and high-level semantic. This model has broad application in lots of domains such as intelligent retrieval engine, medical diagnoses, multimedia design and so on.
