基于大数据的精细化知识服务模型构建

应璇 孙济庆

科研管理 ›› 2016, Vol. 37 ›› Issue (10) : 153-160.

科研管理 ›› 2016, Vol. 37 ›› Issue (10) : 153-160.
论文

基于大数据的精细化知识服务模型构建

  • 应璇,孙济庆
作者信息 +

Model of the refined knowledge services and empirical research based on large data

  • Ying Xuan, Sun Jiqing
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文章历史 +

摘要

本文指出传统的知识服务模式仍然是基于固有资源或系统的、针对用户独立兴趣所开展的“点对点”式粗放型静态服务,效率偏低;而用户的研究进程是动态的,存在明显的需求漂移状态,形成动态连续过程。因此提出精细化知识服务概念,围绕用户学术研究进程,动态跟踪用户需求在不同研究进度中的转移情况,以“面对面”的知识空间形式大大提高知识服务的效果,并通过实验研究的方法验证了用户需求漂移及知识空间的形成,以及论文所提出问题的理论意义和实际意义。

Abstract

This paper points out that the traditional knowledge service model is still on the base of the inherent resources or system, and its service is “point-to-point” extensive static service specific to users independent interests, which is low efficiency; however, the users’ research process is dynamic, there is a significant demand shift state, forming a dynamic continuous process. Thus proposed the concept of Elaborating Knowledge Service, based on users’ academic research process, this paper would dynamic trace the demand shift state of users in different study process, using “face-to-face” knowledge space to greatly improve the effect of knowledge service, and through experimental study validate the formation of user demand shift and knowledge space, as well as the theoretical and practical significance of the issues raised in this paper.

关键词

精细化知识服务 / 研究进程 / 需求漂移 / 知识空间

Key words

refined knowledge service / study process / demand shift / knowledge space

引用本文

导出引用
应璇 孙济庆. 基于大数据的精细化知识服务模型构建[J]. 科研管理. 2016, 37(10): 153-160
Ying Xuan, Sun Jiqing. Model of the refined knowledge services and empirical research based on large data[J]. Science Research Management. 2016, 37(10): 153-160

基金

本文受国家社科基金项目“面向知识服务的学科领域术语语义分析及应用研究”(项目编号:13BTQ053),2013年12月到2016年11月。


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