Query‐centric scientific topic evolution extraction. Issue 1 (24th February 2016)

• Record Type: Journal Article
• Authors: Jensen, Scott; Yu, Yingying; Liu, Hans B.; Liu, Xiaozhong
• Is Part Of: Proceedings of the Association for Information Science and Technology. Volume 52:Issue 1(2015)
• Page Start: 1
• Page End: 4
• Publication Date: 2016-02-24
• Subjects: Topic Evolution -- MeSH -- Heterogeneous Graph; Information science -- Congresses; Information technology -- Congresses; Information science; Information technology; Conference papers and proceedings; 020
• DOI: 10.1002/pra2.2015.1450520100127
• Languages: English
• ISSNs: 2373-9231

Abstract

ABSTRACT: Researchers in academia and industry face a deluge of data in our digital world. In this paper, we investigate a novel problem, query‐centric scientific topic evolution. Using heterogeneous graph mining techniques we construct a topic evolution tree (TET) from massive collections of scientific publications, enabling students and researchers to explore the foundation of research topics outside their specialization. Prior research has focused mainly on citation relationships; in this study we employed multiple types of relationships, including authorship, citation, publishing venue, and the contributions authors, papers, and venues have made to a specific topic. We examine multiple restricted meta‐paths in constructing a TET covering topics from the MeSH vocabulary for biomedical research.