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WIREs Data Mining Knowl Discov
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Tech mining: Text mining and visualization tools, as applied to nanoenhanced solar cells

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Abstract ‘Tech mining’ is a multistep process for the analysis of science, technology, & innovation (‘ST&I’) information resources. It uses text mining, visualization, and communication tools to provide the empirical knowledge necessary to address management of technology questions. Tech mining can help assess mature or emerging fields of science and technology, such as nanotechnology. Here, we depict select analyses and visualizations of relevant ST&I data on the topics of nanoenhanced, thin‐film solar cells and dye‐sensitized solar cells. These analyses help identify complementary and competitive research activity, evaluate research productivity, assess research interdisciplinarity, understand nanotechnology developmental trajectories, and identify and forecast promising nanoapplications. © 2011 John Wiley & Sons, Inc. WIREs Data Mining Knowl Discov 2011 1 172‐181 DOI: 10.1002/widm.7 This article is categorized under: Algorithmic Development > Text Mining Application Areas > Education and Learning Application Areas > Science and Technology Technologies > Visualization

Nanoenhanced thin‐film solar cell publications by research field (from SCI, 2001–2008).

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Nanoenhanced, thin‐film solar cells developmental trajectory template.

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Number of aged nanoenhanced, thin‐film solar cells citations at two points in time relative to the number of articles. Aged citations (ACs) for a country are calculated as ACi = Cti/(Yn−Yt) where Cti = total number of citations for articles in target year for country i; Yn = most recent year in dataset (2008, mid‐year); and Yt = the end of target year. For 2001, Yn−Yt = 6.5; for 2006, Yn−Yt = 1.5. Country is based on the first author's affiliation address.

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Forecasting nanoenhanced, thin‐film solar cells R&D activity trends for the top five countries

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Dye‐sensitized solar cells research collaboration (SCI): segment focusing on Samsung's co‐authoring partners.

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Browse by Topic

Technologies > Visualization
Application Areas > Science and Technology
Algorithmic Development > Text Mining
Application Areas > Education and Learning

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