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International Symposium on Emerging Technologies for Education

SETE 2019: Emerging Technologies for Education pp 201–213Cite as

The Analysis of Worldwide Research on Artificial Intelligence Assisted User Modeling

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Part of the Lecture Notes in Computer Science book series (LNISA,volume 11984)

Abstract

Information and communication technologies is being heralded as a catalyst for educational innovations. Artificial intelligence (AI) assisted user modeling has attracted great increasing interests from the academia with a growing research articles available. In this article, a bibliometric analysis of scientific literature concerning AI assisted user modeling was carried out. 333 articles from Web of Science were retrieved and analyzed to comprehensively understand trends and developments of the research field. Specifically, we analyzed the articles in terms of article count and citation count, influential journals, subjects, authors, and keyword occurrence. Finally, special attention was paid to the study of leading countries/regions and institutions. Findings of this work are useful in helping scholars as well as practitioners better understand the development trend of research of AI assisted user modeling, as well as being more aware of the research hotspots.

Keywords

  • Artificial intelligence
  • User modeling
  • Bibliometric analysis
  • Research hotspots
  • Topic evolution

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References

  1. Mwanza, D., Engeström, Y.: Pedagogical Adeptness in the Design of E-Learning Environments: Experiences from the Lab@ Future project. In: E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education, pp. 1344–1347. AACE (2003)

    Google Scholar 

  2. Leow, F.T., Neo, M.: Interactive multimedia learning: innovating classroom education in a Malaysian University. Turkish Online J. Educ. Technol.-TOJET 13(2), 99–110 (2014)

    Google Scholar 

  3. Papatheocharous, E., Belk, M., Germanakos, P., Samaras, G.: Towards implicit user modeling based on artificial intelligence, cognitive styles and web interaction data. Int. J. Artif. Intell. Tools 23(02), 1440009 (2014)

    CrossRef  Google Scholar 

  4. Brusilovsky, P., Millán, E.: User models for adaptive hypermedia and adaptive educational systems. In: Brusilovsky, P., Kobsa, A., Nejdl, W. (eds.) The Adaptive Web. LNCS, vol. 4321, pp. 3–53. Springer, Heidelberg (2007). https://doi.org/10.1007/978-3-540-72079-9_1

    CrossRef  Google Scholar 

  5. Wu, X., Kumar, V., Quinlan, J.R., Ghosh, J., Yang, Q., Motoda, H., et al.: Top 10 algorithms in data mining. Knowl. Inf. Syst. 14(1), 1–37 (2008)

    CrossRef  Google Scholar 

  6. Mobasher, B.: Data mining for web personalization. In: Brusilovsky, P., Kobsa, A., Nejdl, W. (eds.) The Adaptive Web. LNCS, vol. 4321, pp. 90–135. Springer, Heidelberg (2007). https://doi.org/10.1007/978-3-540-72079-9_3

    CrossRef  Google Scholar 

  7. Pierrakos, D., Paliouras, G., Papatheodorou, C., Spyropoulos, C.D.: Web usage mining as a tool for personalization: a survey. User Model. User-Adap. Inter. 13(4), 311–372 (2003)

    CrossRef  Google Scholar 

  8. Eirinaki, M., Vazirgiannis, M.: Web mining for web personalization. ACM Trans. Internet Technol. (TOIT) 3(1), 1–27 (2003)

    CrossRef  Google Scholar 

  9. Pérez-Acebo, H., Linares-Unamunzaga, A., Abejón, R., Rojí, E.: Research trends in pavement management during the first years of the 21st century: a bibliometric analysis during the 2000–2013 period. Appl. Sci. 8(7), 1041 (2018)

    CrossRef  Google Scholar 

  10. Song, Y., Chen, X., Hao, T., Liu, Z., Lan, Z.: Exploring two decades of research on classroom dialogue by using bibliometric analysis. Comput. Educ. 137, 12–31 (2019)

    CrossRef  Google Scholar 

  11. Chen, X., Wang, S., Tang, Y., Hao, T.: A bibliometric analysis of event detection in social media. Online Inf. Rev. 43(1), 29–52 (2019)

    CrossRef  Google Scholar 

  12. Hao, T., Chen, X., Li, G., Yan, J.: A bibliometric analysis of text mining in medical research. Soft. Comput. 22(23), 7875–7892 (2018)

    CrossRef  Google Scholar 

  13. Chen, X., Liu, Z., Wei, L., Yan, J., Hao, T., Ding, R.: A comparative quantitative study of utilizing artificial intelligence on electronic health records in the USA and China during 2008–2017. BMC Med. Inform. Decis. Mak. 18(5), 117 (2018)

    CrossRef  Google Scholar 

  14. Chen, X., Lun, Y., Yan, J., Hao, T., Weng, H.: Discovering thematic change and evolution of utilizing social media for healthcare research. BMC Med. Inform. Decis. Mak. 19(2), 50 (2019)

    CrossRef  Google Scholar 

  15. Chen, X., Ding, R., Xu, K., Wang, S., Hao, T., Zhou, Y.: A bibliometric review of natural language processing empowered mobile computing. Wireless Communications and Mobile Computing, 2018 (2018)

    Google Scholar 

  16. Chen, X., Xie, H., Wang, F.L., Liu, Z., Xu, J., Hao, T.: A bibliometric analysis of natural language processing in medical research. BMC Med. Inform. Decis. Mak. 18(1), 14 (2018)

    CrossRef  Google Scholar 

  17. Chen, X., Hao, J., Chen, J., Hua, S., Hao, T.: A bibliometric analysis of the research status of the technology enhanced language learning. In: Hao, T., Chen, W., Xie, H., Nadee, W., Lau, R. (eds.) SETE 2018. LNCS, vol. 11284, pp. 169–179. Springer, Cham (2018). https://doi.org/10.1007/978-3-030-03580-8_18

    CrossRef  Google Scholar 

  18. Chen, X., Weng, H., Hao, T.: A data-driven approach for discovering the recent research status of diabetes in China. In: Siuly, S., et al. (eds.) HIS 2017. LNCS, vol. 10594, pp. 89–101. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-69182-4_10

    CrossRef  Google Scholar 

  19. Chen, X., Chen, B., Zhang, C., Hao, T.: discovering the recent research in natural language processing field based on a statistical approach. In: Huang, T.-C., Lau, R., Huang, Y.-M., Spaniol, M., Yuen, C.-H. (eds.) SETE 2017. LNCS, vol. 10676, pp. 507–517. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-71084-6_60

    CrossRef  Google Scholar 

  20. Hassan, S.U., Haddawy, P., Zhu, J.: A bibliometric study of the world’s research activity in sustainable development and its sub-areas using scientific literature. Scientometrics 99(2), 549–579 (2014)

    CrossRef  Google Scholar 

  21. Zawacki-Richter, O., Latchem, C.: Exploring four decades of research in computers & education. Comput. Educ. 122, 136–152 (2018)

    CrossRef  Google Scholar 

  22. Zhong, S., Geng, Y., Liu, W., Gao, C., Chen, W.: A bibliometric review on natural resource accounting during 1995–2014. J. Cleaner Prod. 139, 122–132 (2016)

    CrossRef  Google Scholar 

  23. Gimenez, E., Salinas, M., Manzano-Agugliaro, F.: Worldwide research on plant defense against biotic stresses as improvement for sustainable agriculture. Sustainability 10(2), 391 (2018)

    CrossRef  Google Scholar 

  24. Hirsch, J.E., Buela-Casal, G.: The meaning of the H-Index. Int. J. Clin. Health Psychol. 14(2), 161–164 (2014)

    CrossRef  Google Scholar 

  25. Mann, H.B.: Nonparametric tests against trend. Econometrica J. Econometric Soc. 13(3), 245–259 (1945)

    MathSciNet  CrossRef  Google Scholar 

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Acknowledgements

This work was supported by National Natural Science Foundation of China (No.61772146).

Author information

Authors and Affiliations

  1. Department of Mathematics and Information Technology, The Education University of Hong Kong, Hong Kong SAR, China

    Xieling Chen

  2. School of Information Science and Technology, Guangdong University of Foreign Studies, Guangzhou, China

    Dongfa Gao

  3. Guangzhou Huagong Information Software Co., LTD., Guangzhou, China

    Yonghui Lun

  4. School of Computer Science, South China Normal University, Guangzhou, China

    Dingli Zhou & Tianyong Hao

  5. Department of Computing and Decision Sciences, Lingnan University, Hong Kong SAR, China

    Haoran Xie

Authors
  1. Xieling Chen
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  2. Dongfa Gao
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  3. Yonghui Lun
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  4. Dingli Zhou
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  5. Tianyong Hao
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  6. Haoran Xie
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Corresponding authors

Correspondence to Tianyong Hao or Haoran Xie .

Editor information

Editors and Affiliations

  1. University of Craiova, Craiova, Romania

    Elvira Popescu

  2. South China Normal University, Guangzhou, China

    Tianyong Hao

  3. National Taiwan Normal University, Taipei, Taiwan

    Dr. Ting-Chia Hsu

  4. Lingnan University, Hong Kong, Hong Kong

    Haoran Xie

  5. Sapienza University of Rome, Rome, Italy

    Marco Temperini

  6. Chinese Academy of Agricultural Sciences, Beijing, China

    Wei Chen

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Chen, X., Gao, D., Lun, Y., Zhou, D., Hao, T., Xie, H. (2020). The Analysis of Worldwide Research on Artificial Intelligence Assisted User Modeling. In: Popescu, E., Hao, T., Hsu, TC., Xie, H., Temperini, M., Chen, W. (eds) Emerging Technologies for Education. SETE 2019. Lecture Notes in Computer Science(), vol 11984. Springer, Cham. https://doi.org/10.1007/978-3-030-38778-5_23

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  • DOI: https://doi.org/10.1007/978-3-030-38778-5_23

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