基于学者社交网络的论文与项目关联模型

Association model of paper and project based on scholar social network

针对学者社交网络的独特用户,提出一种基于学者社交网络的论文与项目数据的协同关联模型。首先采用两步特征选择方法预处理数据,去除无关和冗余特征,得到影响论文与项目关联的有效特征;然后通过文本向量空间模型TVSM(text vector space model)计算论文与项目之间的文本相似度,为不同的论文/项目形成推荐集合。通过面向科研人员的社交网络(学者网)数据,实现模型并真实应用于学者网。在线应用情况和用户反馈表明,该模型具有较好的准确性和实用性,可更加充分地挖掘论文与项目之间蕴涵的丰富信息,给用户提供更加高效方便的学术科研管理服务,为分析学术大数据提出了新颖的研究方法。

Considering the unique users of scholars’social networks,this paper proposed a collaborative association model of paper and project data based on scholars’social networks.Firstly,the proposed model used the two-step feature selection method to preprocess the data,removed the irrelevant and redundant features and obtained the effective features that affected the association between the paper and the project.Then it would adopt/TVSM to calculate the text similarity between the paper for researchers,the model was implemented and applied to SCHOLAT.The online application situation and user feedback show that the model has good accuracy and practicability.Furthermore,it can more fully explore the potential relationship between the paper and the project,provide users with better academic research management services,and propose a novel research method for analyzing the academic big data.