分类:AllenAI系列科学学文章

AllenAI 的Semantic Scholar项目提供了免费的论文信息查询，并且希望能够进一步基于论文内容来做帮助科学家开展研究的服务。其背后是AllenAI的研究项目“Understanding and Extracting Information from Scientific Papers” ，“Knowledge Graphs and Ontologies”，　“Science of Science studies”，“Academic Paper Recommendation and Search”。更多细节请访问AllenAI的研究课题页面。

在这里，我们选择其中的一部分文章做一个整理和分享。

Identifying Meaningful Citations

Valenzuela, M. et al. “Identifying Meaningful Citations.” AAAI Workshop: Scholarly Big Data (2015).

We introduce the novel task of identifying important citations in scholarly literature, i.e., citations that indicate that the cited work is used or extended in the new effort. We believe this task is a crucial component in algorithms that detect and follow research topics and in methods that measure the quality of publications.　We model this task as a supervised classification problem at two levels of detail: a coarse one with classes (important vs. non-important), and a more detailed one with four importance classes. We annotate a dataset of approximately 450 citations with this information, and release it publicly. We propose a supervised classification approach that addresses this task with a battery of features that range from citation counts to where the citation appears in the body of the paper, and show that,our approach achieves a precision of 65% for a recall of 90%.

论文研究了“真引用的识别”，并且对引用做了“背景性、方法性、结果性”的分类。同时，论文标注了一些数据，可以供进一步研究。另一方面，其实，这个标记数据数量相当少。在另一些工作里面，例如