无监督预测引文影响Unsupervised Prediction of Citation Influences |
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课程网址: | http://videolectures.net/icml07_dietz_upc/ |
主讲教师: | Laura Dietz |
开课单位: | 马克斯普朗克研究所 |
开课时间: | 2007-06-23 |
课程语种: | 英语 |
中文简介: | 出版物库包含有关科学研究领域发展的大量信息。我们解决了创建研究领域可视化的问题,该研究领域描述了论文之间的主题流,量化了论文对彼此的影响,并有助于确定关键贡献。为此,我们设计了一个解释文档生成的概率主题模型;该模型通过引用融合了主题创新和主题继承的各个方面。我们评估模型预测引用对手动评级引用的影响强度的能力。 |
课程简介: | Publication repositories contain an abundance of information about the evolution of scientific research areas. We address the problem of creating a visualization of a research area that describes the flow of topics between papers, quantifies the impact that papers have on each other, and helps to identify key contributions. To this end, we devise a probabilistic topic model that explains the generation of documents; the model incorporates the aspects of topical innovation and topical inheritance via citations. We evaluate the model's ability to predict the strength of influence of citations against manually rated citations. |
关 键 词: | 出版物库; 论文; 解释文档 |
课程来源: | 视频讲座网 |
最后编审: | 2019-04-17:lxf |
阅读次数: | 48 |