摘要
针对现有多数语义Web服务发现方法应用实施难度大和对终端用户输入信息的完整性依赖度高的问题,提出一种基于简单查询语句的轻量级语义Web服务发现模型。该模型将用户输入的查询语句经过领域本体匹配、基于WordNet同义词典匹配等步骤,自动发现并调用相应的Web服务操作。实验结果表明,采用该服务发现模型能够有效提高服务发现的准确率和召回率,进而可推广应用到基于语义Web服务的农业信息化中。
Amodel for lightweight semantic web service discovery based on user query is proposed according to the problem of most of current semantic-based web service discovery methods that is of great inconvenience to be used and is too dependent on the information inputted by end user.This model provides a user query interface and the according Web service operations will be discovered and be invocated automatically through the process of domain-specific ontologies matching and thesaurus matching based on WordNet dictionary if the user query is inputted.What＇s more,self-learning mechanism is used to enrich ontologies vocabularies in order to enhance the precision rate and recall rate.A serial of experiments illustrate the technologies of domain-specific ontologies matching and self-learning mechanism increases the precision rate and recall rate,and will be widely applied in agricultural information construction.
出处
《农机化研究》
北大核心
2011年第8期134-137,共4页
Journal of Agricultural Mechanization Research
基金
国家自然基金项目(61003168)
山东省自然科学基金项目(Y2007G52)
关键词
农业信息化
WEB服务发现
WORDNET
自学机制
agricultural information construction
Web service discovery
WordNet
self-learning mechanis
