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作 者:何喜军[1] 马珊 武玉英[1] 蒋国瑞[1] He Xijun;Ma Shan;Wu Yuying;Jiang Guorui(School of Economic and Management,Beijing University of Technology,Beijing 100124)
机构地区:[1]北京工业大学经济与管理学院
出 处:《情报杂志》2019年第6期174-181,共8页Journal of Intelligence
基 金:北京市自然科学基金面上项目“基于技术交易数据的京津冀科技协同创新潜力挖掘”(编号:9172002)研究成果之一
摘 要:[目的/意义]为解决在线技术转移平台中因供需信息表述非结构化、供需文本特征稀疏等导致供需文本匹配难的问题,开展线上技术供需信息匹配研究。[方法/过程]提出融合供需文本词频特征、相关性特征和语义特征的匹配模型,通过采集在线技术转移平台(技E网)数据,并针对京津冀技术需求进行供给匹配。[结果/结论]第一,融合多特征的技术供需文本匹配模型,其准确率相比单一特征明显提高;第二,实证研究发现京津冀技术供需文本匹配率为45.437%,但92.5%的供需文本匹配值在0.6左右,匹配值较低,且三地匹配率存在显著差异,河北技术需求在线对接难度更大;第三,技术供需匹配中领域交叉特征不明显,但地理邻近性特征明显。[Purpose/Significance]In order to solve the problem that supply and demand texts are difficult to match mainly because of the unstructured representation of supply and demand information and the sparse feature of supply and demand text,the online technology supply and demand information matching research is carried out.[Method/Process]This paper proposes a matching model that integrates word frequency features,correlation features and semantic features of supply and demand texts.By collecting the data of the online technology transfer platform(technical E network),this paper matches the demand technology in Beijing-Tianjin-Hebei region.[Result/Conclusion]The results show that:firstly,the accuracy of the text matching model for technical supply and demand combined with multiple features is significantly higher than that of single features.Secondly,the empirical study finds that the comprehensive matching rate of technology supply and demand on the platform in Beijing-Tianjin-Hebei region is 45.437%,92.3% of the text matching degree between supply and demand value is at around 0.6,matching degree is low,and the matching rate of the three places is significantly different and the technical demand in Hebei is more difficult.Thirdly,the cross features of the fields are not obvious in the technology supply and demand matching,but the geographical proximity features are obvious.
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