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Using “Text Mining” Analysis for the Assessment of the Health Quality of Dietary Supplements Cover

Using “Text Mining” Analysis for the Assessment of the Health Quality of Dietary Supplements

Open Access
|Dec 2020

References

  1. Aggarwal, C. C., & Zhai, C. (Eds.). (2012). Mining text data. Springer Science & Business Media.10.1007/978-1-4614-3223-4
  2. Dang, S., & Ahmad, P. H. (2014). Text mining: Techniques and its application. International Journal of Engineering & Technology Innovations, 1(4), 866–2348.
  3. Erhardt, R. A., Schneider, R., & Blaschke, C. (2006). Status of text-mining techniques applied to biomedical text. Drug discovery today, 11(7–8), 315–325.10.1016/j.drudis.2006.02.011
  4. Główny Inspektorat Sanitarny. (2019). Rejestr produktów objętych powiadomieniem o pierwszym wprowadzeniu do obrotu na terytorium Rzeczypospolitej Polskiej. Retrived from: http://rejestrzp.gis.gov.pl (access: 2019-12-13).
  5. Główny Inspektorat Sanitarny. (2020). Rejestr produktów objętych powiadomieniem o pierwszym wprowadzeniu do obrotu. Retrived from: http://powiadomienia.gis.gov.pl
  6. Gupta, V., & Lehal, G. S. (2009). A survey of text mining techniques and applications. Journal of emerging technologies in web intelligence, 1(1), 60–76.10.4304/jetwi.1.1.60-76
  7. Harmston, N., Filsell, W., & Stumpf, M. P. (2010). What the papers say: Text mining for genomics and systems biology. Human genomics, 5(1), 17.10.1186/1479-7364-5-1-17
  8. Karl, A., Wisnowski, J., & Rushing, W. H. (2015). A practical guide to text mining with topic extraction. Wiley Interdisciplinary Reviews: Computational Statistics, 7(5), 326–340.10.1002/wics.1361
  9. Khan, Z., & Qamar, U. (2016). Text Mining Approach to Detect Spam in Emails. In The International Conference on Innovations in Intelligent Systems and Computing Technologies (ICIISCT2016) (p. 45).
  10. Koh, J. X., & Liew, T. M. (2020). How loneliness is talked about in social media during COVID-19 pandemic: text mining of 4,492 Twitter feeds. Journal of Psychiatric Research, Nov 07. doi: 10.1016/j.jpsychires.2020.11.01510.1016/j.jpsychires.2020.11.015
  11. Leser, U., & Hakenberg, J. (2005). What makes a gene name? Named entity recognition in the biomedical literature. Briefings in bioinformatics, 6(4), 357–369.10.1093/bib/6.4.357
  12. Mathioudakis, B. (2005). The Emerging Regulatory Environment for Food Supplements in the EU. Food Supplements in Europe: Chllenges for the Future. BLL, EHPM, ERNA, IADSA Conference Report. Retrieved from: https://www.lebensmittelverband.de/download/food-supplements-eu.pdf.
  13. Munková, D., Munk, M., & Vozár, M. (2013). Data pre-processing evaluation for text mining: transaction/sequence model. Procedia Computer Science, 18, 1198–1207.10.1016/j.procs.2013.05.286
  14. Najwyższa Izba Kontroli. (2017). Informacja o wynikach kontroli dopuszczanie do obrotu suplementów diety. Retrieved from: https://www.nik.gov.pl/plik/id,13031,vp,15443.pdf
  15. Petkova-Gueorguieva, E. S., Getov, I. N., Ivanov, K. V., Ivanova, S. D., Gueorguiev, S. R., Getova, V. I., Mihaylova, A. A. et al. (2019). Regulatory requirements for food supplements in the European Union and Bulgaria. Folia medica, 61(1), 41–48.10.2478/folmed-2018-0032
  16. Plisson, J., Lavrac, N., & Mladenic, D. (2004). A rule based approach to word lemmatization. In Proceedings of IS, 3, pp. 83–86.
  17. Restani, P., Di Lorenzo, C., Garcia-Alvarez, A., Badea, M., Ceschi, A., Egan, B., Dima, L. et al. (2016). Adverse effects of plant food supplements self-reported by consumers in the PlantLIBRA survey involving six European countries. PLoS One, 11(2), e0150089.10.1371/journal.pone.0150089
  18. Sahadevan, S., Hofmann-Apitius, M., Schellander, K., Tesfaye, D., Fluck, J., & Friedrich, C. M. (2012). Text mining in livestock animal science: introducing the potential of text mining to animal sciences. Journal of animal science, 90(10), 3666–3676.10.2527/jas.2011-4841
  19. Silano, V., Coppens, P., Larrańaga-Guetaria, A., Minghetti, P., & Roth-Ehrang, R. (2011). Regulations applicable to plant food supplements and related products in the European Union. Food & function, 2(12), 710–719.10.1039/c1fo10105f
  20. Tunali, V., & Bilgin, T. T. (2012). PRETO: A high-performance text mining tool for preprocessing turkish texts. In Proceedings of the 13th International Conference on Computer Systems and Technologies (pp. 134–140).10.1145/2383276.2383297
  21. Ustawa z dnia 11 maja 2001 r. o warunkach zdrowotnych żywności i żywienia. (2001). Dz. U. Nr 63, poz. 634. Retrieved from https://sip.lex.pl/#/act/16901910/170388/warunki-zdrowotne-zywnosci-i-zywienia?cm=SREST.
  22. Ustawa z dnia 25 sierpnia 2006 r. o bezpieczeństwie żywności i żywienia. (2006). Dz. U. z 2020 r. poz. 2021. Retrieved from https://sip.lex.pl/#/act/17302608/2844276/bezpieczenstwo-zywnosci-i-zywienia?keyword=Bezpiecze%C5%84stwo%20%C5%BCywno%C5%9Bci%20i%20%C5%BCywienia&cm=SFIRST.
  23. Vijaymeena, M. K., & Kavitha, K. (2016). A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal, 3(2), 19–28.
  24. Weiss, S. M., Indurkhya, N., Zhang, T., & Damerau, F. (2010). Text mining: predictive methods for analyzing unstructured information. Springer Science & Business Media.
  25. Zhou, X., Han, H., Chankai, I., Prestrud, A., & Brooks, A. (2006). Approaches to text mining for clinical medical records. In Proceedings of the 2006 ACM symposium on Applied computing (pp. 235–239). https://doi.org/10.1145/1141277.114133010.1145/1141277.1141330
DOI: https://doi.org/10.2478/slgr-2020-0037 | Journal eISSN: 2199-6059 | Journal ISSN: 0860-150X
Language: English
Page range: 15 - 26
Published on: Dec 31, 2020
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year
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© 2020 Kacper Wróbel, Anna Justyna Milewska, published by University of Białystok
This work is licensed under the Creative Commons Attribution 4.0 License.