Researchers have largely focused on analyzing citation links from one scholarly work to another. Such citing sentences are an important part of the narrative in a research article. If we can automatically identify such sentences, we can devise an editor that helps suggest when a particular piece of text needs to be backed up with a citation or not. In terms of this point, we propose a method for identifying citing sentences by constructing a classifier using supervised learning.
Proceeding of the 2nd Joint Workshop on Bibliometric-enhanced Information Retrieval and Natural Language Processing for Digital Libraries (BIRNDL@SIGIR), CEUR, Tokyo, Japan, 2017.
Journal of the Association for Information Science and Technology, 2017.
Proceedings of the 2010 International Conference on Information Retrieval and Knowledge Management (CAMP '10), 2010.