A large semantic gap exists between content based index retrieval(CBIR) and high-level semantic,additional semantic information should be attached to the images,it refers in three respects including semantic represent...A large semantic gap exists between content based index retrieval(CBIR) and high-level semantic,additional semantic information should be attached to the images,it refers in three respects including semantic representation model,semantic information building and semantic retrieval techniques.In this paper,we introduce an associated semantic network and an automatic semantic annotation system.In the system,a semantic network model is employed as the semantic representation model,it uses semantic Key words,linguistic ontology and low-level features in semantic similarity calculating.Through several times of users' relevance feedback,semantic network is enriched automatically.To speed up the growth of semantic network and get a balance annotation,semantic seeds and semantic loners are employed especially.展开更多
目的针对目前数据库在提供组织、存储和展示文献来源的蛋白质相互作用知识和数据支撑方面的不足,设计并构建了蛋白质相互作用信息数据库系统(protein-protein interaction information database,dbPPII)。方法根据文献来源的蛋白质相互...目的针对目前数据库在提供组织、存储和展示文献来源的蛋白质相互作用知识和数据支撑方面的不足,设计并构建了蛋白质相互作用信息数据库系统(protein-protein interaction information database,dbPPII)。方法根据文献来源的蛋白质相互作用数据的特点,使用MySQL设计包含蛋白质相互作用、文献及本体三方面信息的数据库结构,引入本体工具展示数据,并使用JSP等技术开发实现。结果数据库系统实现了基于本体的信息组织和展示,提供多种数据查询方式及丰富的文献信息,并具有数据下载功能。目前,dbPPII系统已经应用于组织、存储和展示人及小鼠肝脏相关文献挖掘得到的蛋白质相互作用信息。结论 dbPPII系统具有存储和检索文献来源的蛋白质相互作用信息的多种优势,并有效地利用了蛋白质相互作用本体信息框架组织和展示蛋白质相互作用数据。dbPPII访问主页:http://ppii.hupo.org.cn。展开更多
文摘A large semantic gap exists between content based index retrieval(CBIR) and high-level semantic,additional semantic information should be attached to the images,it refers in three respects including semantic representation model,semantic information building and semantic retrieval techniques.In this paper,we introduce an associated semantic network and an automatic semantic annotation system.In the system,a semantic network model is employed as the semantic representation model,it uses semantic Key words,linguistic ontology and low-level features in semantic similarity calculating.Through several times of users' relevance feedback,semantic network is enriched automatically.To speed up the growth of semantic network and get a balance annotation,semantic seeds and semantic loners are employed especially.
文摘目的针对目前数据库在提供组织、存储和展示文献来源的蛋白质相互作用知识和数据支撑方面的不足,设计并构建了蛋白质相互作用信息数据库系统(protein-protein interaction information database,dbPPII)。方法根据文献来源的蛋白质相互作用数据的特点,使用MySQL设计包含蛋白质相互作用、文献及本体三方面信息的数据库结构,引入本体工具展示数据,并使用JSP等技术开发实现。结果数据库系统实现了基于本体的信息组织和展示,提供多种数据查询方式及丰富的文献信息,并具有数据下载功能。目前,dbPPII系统已经应用于组织、存储和展示人及小鼠肝脏相关文献挖掘得到的蛋白质相互作用信息。结论 dbPPII系统具有存储和检索文献来源的蛋白质相互作用信息的多种优势,并有效地利用了蛋白质相互作用本体信息框架组织和展示蛋白质相互作用数据。dbPPII访问主页:http://ppii.hupo.org.cn。
