摘要
在调研国内外专家识别推荐研究和我国主要专家库的基础上,从专家匹配、抽取规则、专家回避、专家评价和专家排序等5个方面总结归纳了我国现有专家识别推荐系统的主要问题。针对这些问题,考虑系统的可操作性,构建了包括基于知识信息的专家匹配子模块、基于整数线性规划的抽取规则子模块、关系量化的专家回避子模块、结合科学计量学指标与社会网络关系指标的专家评价子模块和综合考虑内容相似度、利益相关度、学术权威度等多条件约束的专家排序子模块的专家识别推荐模块技术框架。该技术框架可实现科技项目小同行评审专家自动识别推荐,得到最优的项目专家分配组合,更全面客观的专家回避处理,综合考虑多条件约束的专家遴选能更好地满足用户需求。
Based on the research of expert recommendation and the current states of the expert database of China, this paper summarized the main problems of the expert system from different perspectives such as domain expert matching, extraction rule, expert avoidance, expert evaluation and expert ranking. Taking into account the operability of the model, we built a technology framework, which contains the submodules like domain expert matching, extraction rule, expert avoidance, expert evaluation and expert ranking, to address these existing problems. With the guidance of this technology framework, we can satisfy the needs of consumers better.
作者
潘云涛
苏成
赵筱媛
王运红
程薛柯
袁军鹏
Pan Yuntao Su Cheng Zhao Xiaoyuan Wang Yunhong Cheng Xuke Yuan Junpeng(Institute of Scientific and Technical Information of China, Beijing 100038)
出处
《情报学报》
CSSCI
北大核心
2016年第9期923-931,共9页
Journal of the China Society for Scientific and Technical Information
基金
国家科技支撑计划项目(2015BAH25F01)
关键词
专家识别推荐
专家匹配
专家回避
专家评价
专家排序
expert recommendation, expert matching, expert avoidance, expert evaluation, expert ranking
