title: Enriching PubMed related article search with sentence level co-citations.
abstract: PubMed related article links identify closely related articles and enhance our ability to navigate the biomedical literature. They are derived by calculating the word similarity between two articles, relating articles with overlapping word content. In this paper, we propose to enrich PubMed with a new type of related article link based on citations within a single sentence (i.e. sentence level co-citations or SLCs). Using different similarity metrics, we demonstrated that articles linked by SLCs are highly related. We also showed that only half of SLCs are found among PubMed related article links. Additionally, we discuss how the citing sentence of an SLC explains the connection between two articles.
authors.affiliation: Department of Pathology, Yale University, New Haven, CT 06520, USA.
authors.forename: Nam
authors.initials: N
authors.lastname: Tran
authors.forename: Pedro
authors.initials: P
authors.lastname: Alves
authors.forename: Shuangge
authors.initials: S
authors.lastname: Ma
authors.forename: Michael
authors.initials: M
authors.lastname: Krauthammer
mesh_terms: D016247:Information Storage and Retrieval / Q000379:methods*; D009323:Natural Language Processing; D039781:PubMed; D009626:Terminology as Topic