摘要
为了实现读者需求知识获取的精准化与动态联动,达到知识重用的目标,文章利用语义分析及智能分词等技术,将读者-资源-标准关键词库进行匹配和过滤,通过读者特征建模、读者层次特征提取、相似读者群建模、读者与相似读者群之间的相似度计算,将相关需求知识推送给读者。实现用相似读者群的需求偏好代替该读者需求偏好,进而将原来无法匹配到的读者需求,通过相似读者群匹配推送给该读者,从而完成读者潜在需求的推送。
In order to realize the precision and dynamic linkage of acquisition of reader demands knowledge and achieve the goal of knowledge reuse, the characteristic data of reader demands are collected from the library service system. By using semantic analysis and intelligent word segmentation and other technologies, the paper matches and filters the reader-resource-standard keywords lists, and pushes the relevant demand knowledge to readers through reader feature modeling, reader hierarchical feature extraction, similar reader group modeling, and similarity calculation between readers and similar reader groups. The demand preference of readers is replaced by the demand preference of similar readers so that the reader demands that cannot be matched before are realized through the matching of similar readers, so as to complete the push of the reader’s potential demands.
出处
《图书馆理论与实践》
CSSCI
2019年第11期107-112,共6页
Library Theory and Practice
基金
山东省社会科学规划项目“数字图书馆语义关联可视化实现研究”(项目编号:15CTQJ01)
山东省文化厅项目“实施乡村振兴战略背景下农村公共文化服务供给驱动与需求引导研究”(项目编号:201806514)的阶段性成果
关键词
读者需求
需求匹配
需求推送
推送路径
Reader Demand
Demand Matching
Demand Pushing
Pushing Path
