Comprehensive Analysis of H2020 Funding Participation based on LDA Topic Modeling and Robust Outlier Identification
文献类型： 会议论文
第一作者： Ferenc Tolner
作者： Ferenc Tolner 1 ; Balázs Barta 2 ; Gy?rgy Eigner 3 ;
作者机构： 1.Pannon Business Network Association, óbuda University Doctoral School of Applied Informatics and Applied Mathematics, Szombathely, Hungary
2.Pannon Business Network Association, Szombathely, Hungary
3.University Research and Innovation Center, Physiological Controls Research Center, óbuda University, Biomatics and Applied Artificial Intelligence Institution, John von Neumann Faculty of Informatics, óbuda University, Budapest, Hungary
关键词： Analytical models;Technological innovation;Social networking (online);Intelligent systems;Informatics;Resilience
会议名称： IEEE Jubilee International Symposium on Intelligent Systems and Informatics
主办单位：
页码： 327-332
摘要： Being able to participate in Horizon 2020 research projects is an outstanding opportunity for innovation and development. Regions can also utilize incorporated knowledge, equipment, added value etc., furthermore can increase their overall competitiveness and resiliency in the long run. Corresponding literature actively investigates the formed social network of project members, central players and possible factors that might contribute to a successful project submission. In the present study freely accessible project information are analysed in combination with regional attributes based on the Minimum Covariance Determinant method. Results are supplemented with results of LDA topic modeling of textual project descriptions. Regional distribution of main project topics are provided and robust outliers are identified with regards of financial funding that indicates major differences between member states connected before 2004 and after.
分类号： tp391
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