Automatically classifying the role of citations in biomedical articles.
Year: 2010
Type: article
Abstract: Citations are widely used in scientific literature. The traditional model of referencing considers all citations to be the same; however, semantically, citations play different roles. By studying the context in which citations appear, it is possible to determine the role that they play. Here, we report on the development of an eight-category classification scheme, annotation using that scheme, and development and evaluation of supervised machine-learning classifiers using the annotated data. We annotated 1,710 sentences using the annotation schema and our trained classifier obtained an average F1-score of 76.5%. The classifier is available for free as a Java API from http://citation.askhermes.org.
Source: PubMed Central
Authors: Shashank Agarwal, Lisha Choubey, Hong Yu
Institution: University of Wisconsin–Milwaukee
Language: English
Subfield: Health Informatics
Field: Medicine
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W141719311