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Semantic Changepoint Detection for Finding Potentially Novel Research Publications.
Dinakar, Bhavish; Boguslav, Mayla R; Görg, Carsten; Dinakarpandian, Deendayal.
Affiliation
  • Dinakar B; Department of Chemical and Biomolecular Engineering, University of California, Berkeley, Berkeley, CA 94720, USA, bhavishdinakar@berkeley.edu.
Pac Symp Biocomput ; 26: 107-118, 2021.
Article in En | MEDLINE | ID: mdl-33691009
How has the focus of research papers on a given disease changed over time? Identifying the papers at the cusps of change can help highlight the emergence of a new topic or a change in the direction of research. We present a generally applicable unsupervised approach to this question based on semantic changepoints within a given collection of research papers. We illustrate the approach by a range of examples based on a nascent corpus of literature on COVID-19 as well as subsets of papers from PubMed on the World Health Organization list of neglected tropical diseases. The software is freely available at: https://github.com/pdddinakar/SemanticChangepointDetection.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Semantics / COVID-19 Type of study: Diagnostic_studies / Prognostic_studies Limits: Humans Language: En Journal: Pac Symp Biocomput Journal subject: BIOTECNOLOGIA / INFORMATICA MEDICA Year: 2021 Document type: Article Country of publication:

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Semantics / COVID-19 Type of study: Diagnostic_studies / Prognostic_studies Limits: Humans Language: En Journal: Pac Symp Biocomput Journal subject: BIOTECNOLOGIA / INFORMATICA MEDICA Year: 2021 Document type: Article Country of publication: