Electrochemical power text mining using bibliometrics and database tomography

Database tomography (DT) is a textual database analysis system consisting of two major components: (1) algorithms for extracting multi-word phrase frequencies and phrase proximities (physical closeness of the multi-word technical phrases) from any type of large textual database, to augment (2) inter...

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Bibliographic Details
Published inJournal of power sources Vol. 110; no. 1; pp. 163 - 176
Main Authors Kostoff, Ronald N, Tshiteya, Rene, Pfeil, Kirstin M, Humenik, James A
Format Journal Article
LanguageEnglish
Published Lausanne Elsevier B.V 20.07.2002
Elsevier Sequoia
Subjects
Applied sciences
Bibliometric analysis
Capacitors. Resistors. Filters
Database tomography
Direct energy conversion and energy accumulation
Electrical engineering. Electrical power engineering
Electrical power engineering
Electrochemical conversion: primary and secondary batteries, fuel cells
Electrochemical power
Energy
Energy. Thermal use of fuels
Equipments for energy generation and conversion: thermal, electrical, mechanical energy, etc
Exact sciences and technology
Fuel cells
Information retrieval
Technical intelligence
Text mining
Various equipment and components
Text mining
Database tomography
Information retrieval
Technical intelligence
Bibliometric analysis
Electrochemical power
Textual data
Electrochemical convertor
Taxonomy
Database
Supercapacitor
Fuel cell
Electrochemical storage
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Summary:Database tomography (DT) is a textual database analysis system consisting of two major components: (1) algorithms for extracting multi-word phrase frequencies and phrase proximities (physical closeness of the multi-word technical phrases) from any type of large textual database, to augment (2) interpretative capabilities of the expert human analyst. DT was used to derive technical intelligence from an electrochemical power database derived from the science citation index (SCI). Phrase frequency analysis by the technical domain experts provided the pervasive technical themes of the electrochemical power database, and the phrase proximity analysis provided the relationships among the pervasive technical themes. Bibliometric analysis of the electrochemical power literature supplemented the DT results with author/journal/institution publication and citation data.
ISSN:0378-7753
1873-2755
DOI:10.1016/S0378-7753(02)00233-1