Scientometrics studies in quantitative fashion the evolution of science focusing on the analysis of publications. One of its objectives is the development of information systems that can help to explore the enormous amount of scientific articles unceasingly published. Our study proposes an information system to reconstruct a dynamical knowledge mapping from a functional data analysis perspective. The source database is a diachronic corpus which originates a words×time-points contingency table displaying the frequencies of each keyword in the set of texts grouped by time-points in the observed time span. The information system consists of an information retrieval procedure for keywords’ selection and a two-stage functional clustering to reconstruct the historical evolution of the knowledge field under investigation.

Knowledge mapping by a functional data analysis of scientific articles databases

TREVISANI, MATILDE;TUZZI, ARJUNA
2017

Abstract

Scientometrics studies in quantitative fashion the evolution of science focusing on the analysis of publications. One of its objectives is the development of information systems that can help to explore the enormous amount of scientific articles unceasingly published. Our study proposes an information system to reconstruct a dynamical knowledge mapping from a functional data analysis perspective. The source database is a diachronic corpus which originates a words×time-points contingency table displaying the frequencies of each keyword in the set of texts grouped by time-points in the observed time span. The information system consists of an information retrieval procedure for keywords’ selection and a two-stage functional clustering to reconstruct the historical evolution of the knowledge field under investigation.
2017
SIS 2017. Statistics and Data Science: new challenges, new generations
Società Italiana di Statistica - SIS2017 Statistical Conference "Statistics and Data Science: new challenges, new generations"
978-88-6453-521-0
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3237193
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