Scientific Information Extraction with Semi-supervised Neural Tagging

This paper addresses the problem of extracting keyphrases from scientific articles and categorizing them as corresponding to a task, process, or material. We cast the problem as sequence tagging and introduce semi-supervised methods to a neural tagging model, which builds on recent advances in named entity recognition. Since annotated training data is scarce in this domain, we introduce a graph-based semi-supervised algorithm together with a data selection scheme to leverage unannotated articles. Both inductive and transductive semi-supervised learning strategies outperform state-of-the-art information extraction performance on the 2017 SemEval Task 10 ScienceIE task.Comment: accepted by EMNLP 201

An Analysis of Reader Engagement in Linguistic Research Articles

This study investigated the use of reader engagement in 60 RAs from the international linguistic journal Language Learning Based on the Model of Stance and Engagement and IMRD Structure under Genre Analysis theory findings suggested that there appear a total of 53 1 reader engagement markers per 10 000 words Under IMRD Structure reader engagement markers occur most frequently in Introduction section 76 9 words per 10 000 words followed by Discussion Method and Results There exists a significant difference of the distribution in reader engagement markers among the four sections X2 22 747 df 3 p 001 Under the Model of Stance and Engagement the frequency of Directives category 102 8 times per 10 000 words is highest followed by Appeals to Shared Knowledge Personal Asides Reader Mentions and Questions The distributions of five engagement markers are significantly different within each section X2 109 466 df 4 p 001 X2 268 079 df 3 p 001 X2 234 765 df 4 p 001 X2 600 722 df 4 p 001 A significant difference is found in the overall distribution of five engagement markers among the four sections X2 102 552 df 4 p 001 Meanwhile this study offers suggestions for the teaching of reader engagement in academic writin