摘要
[目的/意义]构建从用户生成数据中凝聚需求情报并将其推送给运营者的完整框架模型,为学术APP平台智能挖掘用户需求提供思路引导。[方法/过程]首先从学术APP用户需求表达状态出发,剖析用户需求表达的三种典型形式;然后结合需求情报要求及需求聚合方法,提出基于用户聚合的用户标签、基于主题聚合的信息需求主题图谱以及基于文本聚合的服务需求摘要三种需求情报生成方式,最后在分析需求情报推送实现路径的基础上形成整体框架模型,并结合具体实验展示原型实例。[结果/结论]简洁的需求情报可有效减轻需求识别负担,聚合的方法为情报的生成提供了技术支撑,基于需求聚合的学术APP用户需求情报推送模型对数据驱动情境下学术APP平台提高决策效率、优化服务水平有重要参考价值。
[Purpose/Significance]To build a complete framework model that condenses demand intelligence from user-generated data and pushes it to operators,providing guidance for academic APP platform to mine user demand intelligently.[Method/Process]Firstly,starting from the expression state of user demand of academic APP,three typical forms of user demand expression are analyzed.Then combined with requirements intelligence requirements and requirements aggregation methods,three requirements intelligence generation methods,namely user tag based on user aggregation,information demand topic map based on topic aggregation and service demand summary based on text aggregation are proposed.Finally,based on the analysis of the implementation path of requirements intelligence push,the overall framework model is formed,and the prototype example is demonstrated by combining with specific experiments.[Result/Conclusion]Concise demand intelligence can effectively reduce the burden of demand identification,and the aggregation method provides technical support for the generation of information.The demand intelligence push model of academic APP users based on demand aggregation is of great reference value for academic APP platform to improve decision efficiency and optimize service level in data-driven situation.
作者
张莉曼
张向先
卢恒
吴雅威
Zhang Liman;Zhang Xiangxian;Lu Heng;Wu Yawei(School of Management,Jilin University,Changchun 130022)
出处
《情报杂志》
CSSCI
北大核心
2020年第7期126-133,共8页
Journal of Intelligence
基金
国家社会科学基金项目“大数据驱动下学术新媒体知识聚合及创新服务研究”(编号:18BTQ085)研究成果之一。
关键词
学术APP
用户需求
需求表达
需求情报
推送模型
academic application
user demand
demand expression
demand intelligence
push model
