A Text Mining Analysis of the Fly Ash Research Trend (2000-2010)

Shiang Hau Wu; Jiann Jong Guo

doi:10.4028/www.scientific.net/AMR.224.8

Paper Titles

Organizing Committee and Preface

Factors Influencing Bonding Strength of Geopolymer-Aggregate Interfacial Transition Zone
p.1

A Text Mining Analysis of the Fly Ash Research Trend (2000-2010)
p.8

Discussion on Guidance Space and Mediation Space Environment Design in Cinema
p.12

Application of Non-Structural Fuzzy Decision Method in Selection of Partners
p.17

Gas Diffusivity in Fractal - Characterized Porous Materials
p.24

Appropriate Sustainable House Design for China’s Countryside
p.29

Transformation of Traditional Industrial Regions into Campus in Sustainable Way
p.34

Ecological Agriculture Technology in Urban Agriculture
p.38

HomeAdvanced Materials ResearchAdvanced Materials Research Vol. 224A Text Mining Analysis of the Fly Ash Research...

A Text Mining Analysis of the Fly Ash Research Trend (2000-2010)

Abstract:

In recent years, much research has been devoted to the fly ash research; however, few have deployed the study of the research trend. In fact, grasping the research trend is imperative for enterprises and researchers. The study aims at exploring the trend change of fly ash research from 2000 to 2010. The contribution of the study includes the following two points. First, the study has found the shift of the fly ash research from shifts from “concrete” and “pulse” related issues to the focuses of “absorption” and “metal”. Second, the study finds a new way of literature survey by using the text mining method in order to explore the trend change.

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Periodical:

Advanced Materials Research (Volume 224)

Pages:

8-11

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.224.8

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Online since:

April 2011

Authors:

Shiang Hau Wu, Jiann Jong Guo

Keywords:

Fly Ash (FA), Konstanz Information Miner (KNIME), Text Mining, Trend

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References

[1] S. Weiss, N. Indukhya, T. Zhang, and F. Damerau, Text Mining: Predictive Method for Analyzing Unstructured Information, Springer( 2005).

Google Scholar

[2] K. Thiel, The KNIME Text Processing Plugin, available at http: /www. knime. org (accessed on May 10, 2010) (2009).

Google Scholar

[3] M.F. Porter, An Algorithm for Suffix Stripping, Computer Laboratory, Cambridge, p.313–316 (1997).

Google Scholar

[4] Y. Matsuo, M. Ishizuka, , Keyword Extraction from a Single Document using Word Co-ocurrence Statistical Information, International Journal on Artificial Intelligence Tools, Vol. 13, No. 1, pp.157-169 (2004).

DOI: 10.1142/s0218213004001466

Google Scholar

[5] K. Thiel, KeyGraph: automatic indexing by co-occurrence graph based on building construction metaphor, IEEE International Forum on Research and Technology Advances in Digital Libraries, ADL 98, Proceedings (1998).

DOI: 10.1109/adl.1998.670375

Google Scholar

[6] M. R. Berthold, B. Wiswedel, and D.E. Patterson, Interactive exploration of fuzzy clusters using neighborgrams, Fuzzy Sets and Systems, Vol. 149, No. 1, p.21–37 (2005).

DOI: 10.1016/j.fss.2004.07.009

Google Scholar

[7] B. Wiswedel, Lernen in Parallelen Universen, Disseration zur Erlangung des akademischen Grades des Doktors der Naturwissenschaften, Universitaet Konstanz (2008).

Google Scholar