Skip to main content
SpringerLink
Log in

Intelligent Decision Support Based on Mental User Models: Research Design

  • Conference paper
  • First Online:
Software Engineering Application in Systems Design (CoMeSySo 2022)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 596))

Included in the following conference series:

Abstract

This paper describes the research design in the field of user modeling for intelligent decision support. The relevance of the research, the novelty and the significance of the research results for the development of a new type of interfaces based on cognitive visualization of spatial data are described. This paper is the first step in a research project aimed at developing new approaches for creating cognitive user interfaces. The paper describes the overall research design, the research problem, the specific tasks within the problem, the scientific novelty of the research, and the expected results. In addition, we give a brief overview of the current state of research on the problem, describe the main directions of research in world science, as well as suggest some methods and approaches to implement the main stages of the project. The duration of the research is two years, the number of performers is three people. Thus, we present a brief overview in the field of intelligent decision support based on mental user models, describe our research strategy and discuss the problems of creating and using mental user models for decision-making purposes.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 149.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 199.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Smirnov, A., Levashova, T., Petrov, M.: Scenario model of intelligent decision support based on user’s digital life models. Inf. Control Syst. 4, 47–60 (2021). https://doi.org/10.31799/1684-8853-2021-4-47-60

    Article  Google Scholar 

  2. Smirnov, A., Ponomarev, A., Levashova, T., Shilov, N.: Conceptual framework of a human-machine collective intelligence environment for decision support. In: Proceedings of the Bulgarian Academy of Sciences, vol. 75, no 1, pp. 102–109 (2022). https://doi.org/10.7546/CRABS.2022.01.12

  3. Araujo, T., Helberger, N., Kruikemeier, S., de Vreese, C.H.: In AI we trust? Perceptions about automated decision-making by artificial intelligence. AI Soc. 35(3), 611–623 (2020). https://doi.org/10.1007/s00146-019-00931-w

    Article  Google Scholar 

  4. Asniar Surendro, K.: Predictive analytics for predicting customer behavior. In: International Conference of Artificial Intelligence and Information Technology (ICAIIT), pp. 230–233. IEEE (2019). https://doi.org/10.1109/ICAIIT.2019.8834571

  5. Vicentiy, A.V., Vicentiy, I.V.: The method of dynamic visualization of spatial data for cognitive interfaces of information systems supporting regional management. In: 19th International Multidisciplinary Scientific Geoconference SGEM 2019, pp. 667–672 (2019). https://doi.org/10.5593/sgem2019/2.1/S07.087

  6. Vicentiy, A.V.: Development of methods and tools to support regional management in the Arctic zone of the Russian Federation based on cognitive interfaces. IOP Conf. Ser.: Earth Environ. Sci. 320, 012139 (2019). IOP Publishing. https://doi.org/10.1088/1755-1315/302/1/012139

  7. Pentland, B.T., Recker, J., Wolf, J., Wyner, G.: Bringing context inside process research with digital trace data. J. Assoc. Inf. Syst. 21(5), 1214–1236 (2020). https://doi.org/10.17705/1jais.00635

    Article  Google Scholar 

  8. Kitchenham, B., Brereton, P.: A systematic review of systematic review process research in software engineering. Inf. Softw. Technol. 55(12), 2049–2075 (2013)

    Article  Google Scholar 

  9. Kitchenham, B., Charters, S.: Guidelines for performing systematic literature reviews in software engineering. Technical report EBSE-2007-01, School of Computer Science and Mathematics, Keele University (2007)

    Google Scholar 

  10. Hevner, A.R., March, S.T., Park, J., Ram, S.: Design science in information systems research. MIS Q.: Manag. Inf. Syst. 28(1), 75–105 (2004). https://doi.org/10.2307/25148625

    Article  Google Scholar 

  11. Wulandari, I.A., Sensuse, D.I., Krisnadhi, A.A., Akmaliah, I.F., Rahayu, P.: Ontologies for decision support system: the study of focus and techniques. In: 10th International Conference on Information Technology and Electrical Engineering (ICITEE), pp. 609–614 (2018). https://doi.org/10.1109/ICITEED.2018.8534947

  12. Kadima, H., Malek, M.: Toward ontology-based personalization of a recommender system in social network. Int. J. Comput. Inf. Syst. Ind. Manag. Appl. 5, 499–508 (2013). https://doi.org/10.1109/SOCPAR.2010.5685957

  13. Pilecki, B.M., Vicentiy, A.V.: Development of a method for extracting spatial data from texts for visualization and information decision-making support for territorial management. IOP Conf. Ser.: Earth Environ. Sci. Institute of Physics Publishing (2020). https://doi.org/10.1088/1755-1315/539/1/012087

  14. Ben Hassen, A., Ben Ticha, S., Chaibi, A.H.: Deep learning for visual-features extraction based personalized user modeling. SN Comput. Sci. 3, 261 (2022). https://doi.org/10.1007/s42979-022-01131-y

    Article  Google Scholar 

  15. Wang, L., Huang, C., Lu, Y., Ma, W., Liu, R., Vosoughi, S.: Dynamic structural role node embedding for user modeling in evolving networks. ACM Trans. Inf. Syst. 40(3), 21, Article 46 (July 2022) (2021). https://doi.org/10.1145/3472955

  16. Fischer, G.: User modeling in human-computer interaction. User Model. User-Adap. Inter. 11(11), 65–86 (2001). https://doi.org/10.1023/A:1011145532042

    Article  MATH  Google Scholar 

  17. Hothi, J., Hall, W.: An evaluation of adapted hypermedia techniques using static user modelling. In: Proceedings of the 2nd Workshop on Adaptive Hypertext and Hypermedia, Southampton University, Electronics and Computer Science University Road, Southampton, Hampshire, UK (1998)

    Google Scholar 

  18. Piao, G., Breslin, J.G.: Inferring user interests in microblogging social networks: a survey. User Model. User-Adap. Inter. (UMUAI). 28(3), 277–329 (2018) arXiv:1712.07691. https://doi.org/10.1007/s11257-018-9207-8. S2CID 3847937

  19. Seeskin, Z.H., et al.: Uses of alternative data sources for public health statistics and policymaking: challenges and opportunities. In: Proceedings of 2018 Joint Statistical Meetings. American Statistical Association, pp. 1822–1861 (2018)

    Google Scholar 

  20. Han, M.L., Kwak, B.I., Kim, H.K.: CBR-based decision support methodology for cybercrime investigation: focused on the data-driven website defacement analysis. Secur. Commun. Netw. 2019 (2019)

    Google Scholar 

  21. Singh, H., Khalajzadeh, H., Paktinat, S., Graetsch, U.M., Grundy, J.: Modelling human-centric aspects of end-users with iStar. J. Comput. Lang. 68, 101091 (2022). https://doi.org/10.1016/j.cola.2022.101091

    Article  Google Scholar 

  22. Grundy, J., Khalajzadeh, H., McIntosh, J., Kanij, T., Mueller, I.: HumaniSE: approaches to achieve more human-centric software engineering. In: Ali, R., Kaindl, H., Maciaszek, L.A. (eds.) Evaluation of Novel Approaches to Software Engineering (ENASE 2020). Communications in Computer and Information Science (CCIS), vol. 1375, pp. 444–468. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-70006-5_18

    Chapter  Google Scholar 

  23. Curumsing, M.K., Fernando, N., Abdelrazek, M., Vasa, R., Mouzakis, K., Grundy, J.: Understanding the impact of emotions on software: a case study in requirements gathering and evaluation. J. Syst. Softw. 147, 215–229 (2019). https://doi.org/10.1016/J.JSS.2018.06.077

    Article  Google Scholar 

  24. Wirtz-Brückner, S., Jakobs, E.-M., Ziefle, M.: Age-specific usability issues of software interfaces. LandLeuchten (BMVI-funded) view project public acceptance and perception of carbon capture and utilization (CCU) view project. Proc. IEA. 17, 1–10 (2009)

    Google Scholar 

  25. Stock, S.E., Davies, D.K., Wehmeyer, M.L., Palmer, S.B.: Evaluation of cognitively accessible software to increase independent access to cellphone technology for people with intellectual disability. J. Intellect. Disabil. Res. 52, 1155–1164 (2008). https://doi.org/10.1111/j.1365-2788.2008.01099.x

    Article  Google Scholar 

  26. Jim, A., Shim, H., Wang, J., Wijaya, L., Xu, R., Khalajzadeh, H., Grundy, J., Kanij, T.: Improving the modelling of human-centric aspects of software systems: a case study of modelling end user age in wirefame designs. In: Proceedings of the 16th International Conference on Evaluation of Novel Approaches to Software Engineering, pp. 68–79. SCITEPRESS—Science and Technology Publications (2021). https://doi.org/10.5220/0010403000680079

  27. Grundy, J., Khalajzadeh, H., Mcintosh, J.: Towards human-centric model-driven software engineering. In: Proceedings of the 15th International Conference on Evaluation of Novel Approaches to Software Engineering, pp. 229–238. SCITEPRESS—Science and Technology Publications (2020). https://doi.org/10.5220/0009806002290238

  28. Vicentiy, A.V.: The geoimage generation method for decision support systems based on natural language text analysis. In: Silhavy, R. (ed.) CSOC 2021. LNNS, vol. 230, pp. 609–619. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-77442-4_51

    Chapter  Google Scholar 

  29. Bahrainian, S.A., Crestani, F.: Tracking smartphone app usage for time-aware recommendation. In: Choemprayong, S., Crestani, F., Cunningham, S.J. (eds.) ICADL 2017. LNCS, vol. 10647, pp. 161–172. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-70232-2_14

    Chapter  Google Scholar 

  30. Jameson, A., Paris, C., Tasso, C. (eds.): User Modeling. ICMS, vol. 383. Springer, Vienna (1997). https://doi.org/10.1007/978-3-7091-2670-7

    Book  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Putilov Institute for Informatics and Mathematical Modeling—Subdivision of the Federal Research Centre, Kola Science Centre of the Russian Academy of Sciences, 24A, Fersman St., Apatity, Murmansk Region, 184209, Russia

    A. V. Vicentiy

  2. Apatity Branch of Murmansk Arctic State University, Lesnaya St. 29, Apatity, Murmansk Region, 184209, Russia

    A. V. Vicentiy

Authors
  1. A. V. Vicentiy
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to A. V. Vicentiy .

Editor information

Editors and Affiliations

  1. Faculty of Applied Informatics, Tomas Bata University in ZlĂ­n, ZlĂ­n, Czech Republic

    Radek Silhavy

  2. Faculty of Applied Informatics, Tomas Bata University in ZlĂ­n, ZlĂ­n, Czech Republic

    Petr Silhavy

  3. Faculty of Applied Informatics, Tomas Bata University in ZlĂ­n, ZlĂ­n, Czech Republic

    Zdenka Prokopova

Rights and permissions

Reprints and permissions

Copyright information

© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Vicentiy, A.V. (2023). Intelligent Decision Support Based on Mental User Models: Research Design. In: Silhavy, R., Silhavy, P., Prokopova, Z. (eds) Software Engineering Application in Systems Design. CoMeSySo 2022. Lecture Notes in Networks and Systems, vol 596. Springer, Cham. https://doi.org/10.1007/978-3-031-21435-6_63

Download citation

Publish with us

Policies and ethics

Search

Navigation