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Autor
Baj-Rogowska Anna (Gdansk University of Technology)
Tytuł
Agile Commerce in the Light of Text Mining
Źródło
Przedsiębiorczość i Zarządzanie, 2017, t. 18, z. 4, cz. 1, s. 85-101, rys., tab., bibliogr. 12 poz.
Entrepreneurship and Management
Tytuł własny numeru
Agile Commerce - świat technologii i integracji procesowej
Słowa kluczowe
Eksploracja tekstu, Handel elektroniczny, Data Mining
Text mining, e-commerce, Data Mining
Uwagi
summ.
Abstrakt
The survey conducted for this study reveals that more than 84% of respondents have never encountered the term "agile commerce" and do not understand its meaning. At the same time, they are active participants of this strategy. Using digital channels as customers more often than ever before, they have already been included in the agile philosophy. Based on the above, the purpose of the study is to analyse major text sets containing the "agile commerce" term, using the text data mining methods and tools. Data for analyses were sourced through creating an "agile commerce" query on websites with English as the content language. The texts retrieved in this way were used for building a corpus of documents. As a result of the corpus text exploration, words appearing most frequently in association with the agile commerce concept were separated and their most typical contexts were identified. The mining of unstructured data - the text mining process - revealed the essential meaning of the term being studied, while exploring knowledge from large information resources. (original abstract)
Pełny tekst
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Bibliografia
Pokaż
  1. Berry M.W. (red.) (2013), Survey of Text Mining: Clustering, Classification, and Retrieval, Springer Science+Business Media, Inc. NY, USA.
  2. Chakraborty G., Pagolu M., Garla S. (2014), Text Mining and Analysis: Practical Methods, Examples, and Case Studies Using SAS, SAS Institute Inc., North Carolina, USA.
  3. E-Commerce w Polsce. Gemius dla e-Commerce Polska (2015), Gemius Polska [online], https://www.gemius.pl/files/reports/E-commerce-w-Polsce-2015.pdf, dostęp: 27.01.2017.
  4. Krawczyk M. (red.) (2012), Ekonomia eksperymentalna, Wolters Kluwer Polska Sp. z o.o., Warszawa.
  5. Metes G., Gundry J., Bradish P. (1998), Agile Networking: Competing Through the Internet and Intranets, Prentice Hall PTR.
  6. Miner G., Elder J., Fast A. i in. (2012), Practical Text Mining and Statistical Analysis for Non-structured Text Data Aplications, Elsevier, UK.
  7. National Research Council (1997), Committee on Technology for Future Naval Forces, Commission on Physical Sciences, Mathematics, and Applications, Division on Engineering and Physical Sciences, "Technology for the United States Navy and Marine Corps, 2000-2035 Becoming a 21st-Century Force", National Academy Press, Washington.
  8. Provalis Research (2017), ProSuite [online], https://provalisresearch.com/products/qualitative-data-analysis-software/, dostęp: 12.01.2017.
  9. Tedd L.A. (2006), Program 1966-2006: Celebrating 40 Years of ICT in Libraries, Museums and Archives, Emerald Group Publishing Limited, UK.
  10. Tuffery S. (2011), Data Mining and Statistics for Decision Making, John Wiley & Sons Ltd., UK.
  11. Urbańska N. (2011), Czy nadchodzi koniec Multichannel Commerce?, Ideas2Action [online], http://ideas2action.pl/2011/04/04/czy-nadchodzi-koniec-multichannel-commerce/, dostęp: 2.01.2017.
  12. Weiss S.M., Indurkhya N., Zhang T. i in. (2010), Text Mining: Predictive Methods for Analyzing Unstructured Information, Springer Science+Business Media Inc., NY.
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ISSN
2543-8190
Język
eng
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