Research Topics Variation Analysis and Prediction Based on FARO and Neural Networks

	Research Topics Variation Analysis and Prediction Based on FARO and Neural Networks
	Zhu, Hongyin1 ; Zeng, Yi1,2 ; Yiping Yang1
	2016-10
会议名称	2016 IEEE International Conference on Systems, Man, and Cybernetics
会议日期	October 9-12, 2016
会议地点	Hungary
出版地	Hungary
出版者	IEEE International Conference on Systems, Man, and Cybernetics
摘要	Given the explosive growth of scientific information and the fast advancement of research fields, researchers may not be able to find the most promising topics to combine with their current research and may be trapped in a few familiar research topics without creative ideas. Many studies of recommendation system make the effort to address the above problem, but they ignore the different styles of users and generate the recommendation results based on a common strategy. In this paper, we propose a framework to generate the adaptive recommendation results according to the research styles of users. Our framework contains 3 main parts, the research topic ontology construction, trend prediction and recommendation. First of all, the Fun of Academic Research Ontology (FARO), which has the capacity of describing dynamic and static research features and building a social network, is constructed to organize entities about academic research. Secondly, this paper predicts the popularity variation of research topics with the neural network model. Finally, some adaptive topics are recommended to specific researchers according to the evaluation of their research styles. Basically, this paper is inspired by the associative thinking of human brain to combine the advantages of Web knowledge representation language and the neural network to execute the prediction and recommendation. We test our results based on the publication data of IEEE and Springer. The experimental results demonstrate that our prediction model has a good generalization performance. A questionnaire survey is carried out to assess the recommendation results, and the result shows the feasibility of our method.
文献类型	会议论文
条目标识符	http://ir.ia.ac.cn/handle/173211/14353
专题	脑图谱与类脑智能实验室_类脑认知计算
作者单位	1.Institute of Automation, Chinese Academy of Sciences, Beijing, China 2.Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China
第一作者单位	中国科学院自动化研究所
推荐引用方式 GB/T 7714	Zhu, Hongyin,Zeng, Yi,Yiping Yang. Research Topics Variation Analysis and Prediction Based on FARO and Neural Networks[C]. Hungary:IEEE International Conference on Systems, Man, and Cybernetics,2016.

条目包含的文件		下载所有文件
文件名称/大小	文献类型	版本类型	开放类型	使用许可
Research Topics Vari（1486KB）	会议论文		开放获取	CC BY-NC-SA	浏览下载