Classification of Photovoltaic Research Papers by Using Text-Mining Techniques

Hyo Seong Lee; Hae Goo Song; Hee Sang Lee

doi:10.4028/www.scientific.net/AMM.284-287.3362

Paper Titles

Analysis and Design of Semantic Web Services Using MDA and SBC Structure
p.3340

Analysis of Convective-Radiative Fins by Using Hybrid Spline Difference Method
p.3345

Analytic Network Process Decision-Making to Downloadable Content System
p.3352

Annotation System for the Construction of Synchronous Grammar Tree Alignment Relationships
p.3357

Classification of Photovoltaic Research Papers by Using Text-Mining Techniques
p.3362

Cloud Based Evolution Algorithm with Feedback Control for Emergency Logistic
p.3370

Cluster Search Engine Results with Crowd Intelligence
p.3375

Cryptanalysis and Improvement of a Unique Batch Authentication Protocol for Vehicle-to-Grid Communications
p.3380

Defend a System against Keyloggers with a Privilege-Limited Account
p.3385

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 284-287Classification of Photovoltaic Research Papers by...

Classification of Photovoltaic Research Papers by Using Text-Mining Techniques

Abstract:

The research described in this article focuses on one important aspect of monitoring scientific and technological trends and tries to examine topics of research and trends in the photovoltaic field. The data used to examine the research and trends were scientific and technological literature published during the last five years, which were exhaustively collected from the two SCI journals that specialize in photovoltaic and solar energy research. In order to analyze the 2,031 academic papers colllected, text-mining was applied. As a result, research topics were identified through document clustering and classified through text categorization into four major subjects; ‘Cell’, ‘Module/Array’, ‘System’ and ‘Relative/Advanced.’

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Periodical:

Applied Mechanics and Materials (Volumes 284-287)

Pages:

3362-3369

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.284-287.3362

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Online since:

January 2013

Authors:

Hyo Seong Lee, Hae Goo Song, Hee Sang Lee

Keywords:

Bibliometric, Classification, Photovoltaic (PV), Research Paper, Text-Mining

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References

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