基于多特征耦合的数字图书馆知识发现服务优化研究

Research on Knowledge Discovery Service Optimization of Digital Library Based on Multi-feature Coupling

[目的/意义]大数据环境下,用户的知识需求由分散向关联转变,利用多特征耦合可以辅助知识发现服务发现资源间的多种相关关系,从而优化知识发现服务。[方法/过程]通过分析文献内部和外部属性特征定义多特征耦合的概念,从功能角度出发,剖析多特征耦合与数字图书馆知识服务之间的关系,结合现有的知识发现系统构建多特征耦合架构,基于数据层-耦合层-服务层三层提出提升知识发现服务供给侧的方法。[结果/结论]数据层保障数据的质量,数据源由单一向混合转变;耦合层提升耦合分析效果,分析单位由粗向细转变,注重细粒度单元间的语义关联;服务层重视用户的交互体验,开发多维可视化功能。

[Purpose/significance ]In the context of big data,the user's knowledge needs are changed from decentralization to correlation,and multi-feature coupling is used to assist the knowledge discovery service to discover multiple correlations between resources,thereby optimizing knowledge discovery services.[Method/process ]The concept of multi-feature coupling was defined by analyzing the internal and external attribute characteristics of the literature.This paper analyzed the relationship between multi-feature coupling and digital library knowledge service according to the function of multi-feature coupling.Then,by combining the existing knowledge discovery system,the multi-feature coupling structure was constructed.And the method of improving the supply side of the knowledge discovery service was proposed based on data layer-coupling layer-service layer.[Result/conclusion]The data layer guarantees the quality of the data,the data source changes from single to mixed;the coupling layer enhances the effect of coupling analysis,the unit of analysis changes from coarse-grained to fine-grained,the semantic association between fine-grained units attracts much attention;the service layer attaches importance to the user's interactive experience and develops multi-dimensional visualization function.