1. Query-Centric Scientific Topic Evolution Extraction.
- Author
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Jensen, Scott, Yu, Yingying, Liu, Hans B., and Liu, Xiaozhong
- Subjects
QUERY (Information retrieval system) ,AUTHORSHIP ,CITATION analysis ,MESH analysis (Electric circuits) ,MEDICAL research ,CITATION networks - 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. [ABSTRACT FROM AUTHOR]
- Published
- 2015
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