Skip to main content

Project Team Recommendation Model Based on Profiles Complementarity

  • Conference paper
  • First Online:
HCI International 2020 – Late Breaking Papers: Cognition, Learning and Games (HCII 2020)

Abstract

An influencing factor in integration and development of a project team is personality trait. Considering the specificities of project teams, which usually requires multidisciplinary knowledge, there was a need to develop a team recommendation system model that considers, in addition to technical characteristics (training, skills, competences, experiences), personality traits of its participants. Some researches have applied personality traits in systems that recommend people, however, the works in this line, make the recommendation based on the principles of similarity of profiles. Thus, the recommendation model proposed in this paper is based on the principle of profile complementarity. The profile complementarity model aims to achieve the best possible personality combination so that one member’s strengths complement the other’s weaknesses. From the proposed model, the prototype of a recommendation system was developed

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
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. Bejarano, V.C.: Como formar equipes com o equilíbrio ideal de personalidades e perfis pessoais: a teoria e as ferramentas de Meredith Belbin. XXXIII Congresso Brasileiro de Ensino de Engenharia (2005)

    Google Scholar 

  2. Belbin, R.M.: Team Roles at Work, 2ª edn. Butterworth Heinemann Oxford, United States (2010)

    Google Scholar 

  3. Nunes, M.A.: Computação Afetiva personalizando interfaces, interações e recomendações de produtos, serviços e pessoas em Ambientes computacionais. In: Nunes, M.; Oliveira, A.A.; Ordonez, E.D.M. (Org.). DCOMP e PROCC: Pesquisas e Projetos, (2012)

    Google Scholar 

  4. Thenmalar, V., Tamilselvi, R., Sandhiya, S., Dhivya, S.M.: Social recommendation for interactive online system. In: International Journal of Science and Research (IJSR), UG Scholar, Department of Computer Science and Engineering, Sri Krishna College of Technology, Coimbatore, TN, India (2017)

    Google Scholar 

  5. Oliveira, G.: Abordagem para Análise de traços de personalidade no apoio à recomendação de equipes de projeto. Monografy(bachelor of Computer Science)–Universidade Estadual do Norte do Paraná (2017)

    Google Scholar 

  6. Boehm, B.W.: Software Engineering Economics. Prentice-Hall, Englewood Cliffs, New Jersey (1981)

    Google Scholar 

  7. Oliveira, G., dos Santos Braz, R., de Freitas Guilhermino Trindade, D., de Fátima Guilhermino, J., Merlin, J.R., Sgarbi, E.M., Ribeiro, C.E., de Oliveira, T.F.: Model for analysis of personality traits in support of team recommendation. In: Sottilare, R.A., Schwarz, J. (eds.) HCII 2019. LNCS, vol. 11597, pp. 405–419. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-22341-0_32

    Chapter  Google Scholar 

  8. Martins, J.C.C.: Gerenciando Projetos de Desenvolvimento de Software com PMI, RUP e UML. 5th ed. Rio de Janeiro, Brasport (2010)

    Google Scholar 

  9. Project Management Institute (PMI). Project Management Body of Knowledge. 5th edn. (2013)

    Google Scholar 

  10. Robillard, M.P., Walker, R.J., Zimmermann, T.: Recommendation systems for software engineering. IEEE Softw. 27(4), 80–86 (2010)

    Article  Google Scholar 

  11. Valdez, A.C., Ziefle, M., Verbert, K.: HCI for recommender systems: the past, the present and the future. In: 10th ACM Conference on Recommender Systems - RecSys’16., Boston, MA, USA (2016) https://doi.org/10.1145/2959100.2959158

  12. Isinkaye, F.O., Folajimi, Y.O., Ojokoh, B.A.: Recommendation systems: principles, methods and evaluation. Egypt. Inform. J. 16(3), 261–273 (2015)

    Article  Google Scholar 

  13. Pazzani, M.J.: A framework for collaborative, content-based and demographic filtering. Artif. Intell. Rev. 13, 393–408 (1999). https://doi.org/10.1023/A:1006544522159

    Article  Google Scholar 

  14. Lops, P., de Gemmis, M., Semeraro, G.: Content-based recommender systems: state of the art and trends. In: Ricci, F., Rokach, L., Shapira, B., Kantor, P.B. (eds.) Recommender Systems Handbook, pp. 73–105. Springer, Boston, MA (2011). https://doi.org/10.1007/978-0-387-85820-3_3

    Chapter  Google Scholar 

  15. Liu, L., Mehandjiev, N., Xu, D.L.: Multi-criteria service recommendation based on user criteria preferences. In: Fifth ACM Conference on Recommender Systems - RecSys’11., Chicago, Illinois, USA. ACM (2011) https://doi.org/10.1145/2043932.2043950

  16. Pimenidis, E., Polatidis, N., Mouratidis, H.: Mobile recommender systems: identifying the major concepts. J. Inf. Sci. University of Brighton, Brighton, UK. 016555151879221 (2018) https://doi.org/10.1177/0165551518792213

  17. Ricci, F., Rokach, L., Shapira, B.: Introduction to recommender systems handbook. In: Ricci, F., Rokach, L., Shapira, B., Kantor, P.B. (eds.) Recommender Systems Handbook, pp. 1–35. Springer, Boston, MA (2011). https://doi.org/10.1007/978-0-387-85820-3_1

    Chapter  MATH  Google Scholar 

  18. Cazella, S. C., Nunes, M. A. S. N., Reategui, E.: A ciência da opinião: estado da arte em sistemas de recomendação. In: André Ponce de Leon F. de Carvalho; Tomasz Kowaltowski.. (Org.). Jornada de Atualização de Informática-JAI - CSBC2010. Rio de Janeiro: PucRIO, vol. 1, pp. 161–216 (2010)

    Google Scholar 

  19. Nunes, M.A.S.N., Moraes, D.B., Reinert, D.: Personality inventory - Pv 1.0 (Portuguese Version). (2010)

    Google Scholar 

  20. Nunes, M.A.S.N., et al.: Computação afetiva e sua influência na personalização de ambientes educacionais: gerando equipes compatíveis para uso em AVAs na EaD. n: Educação e Ciberespaço: Estudos, propostas e desafios ed. Aracaju: Virtus, vol. 1, pp. 308–347 (2010)

    Google Scholar 

  21. Nunes, M.A.S.N., Bezerra, J.S., Reinert, D., Moraes, D., Silva, É.P., Pereira, A.J.: Computação afetiva e sua influência na personalização de ambientes educacionais: gerando equipes compatíveis para uso em AVAs na EaD. Virtus Editora, Educação E Ciberespaço: Estudos, Propostas E Desafios. Aracaju pp. 308–347 (2010)

    Google Scholar 

  22. Mengato Junior, R.C.: Ferramenta de apoio à alocação de equipes em projetos de desenvolvimento de software. Monografia (Bacharelado em Sistemas da Informação)–Universidade Estadual do Norte do Paraná, Paraná p. 41 (2015)

    Google Scholar 

  23. Nascimento, M.: Um modelo de recomendação de equipes de projeto com base na complementaridade de perfis. Monografy(bachelor of Computer Science)–Universidade Estadual do Norte do Paraná (2019)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Bruno Mendonça Santos .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

dos Santos Nascimento, M. et al. (2020). Project Team Recommendation Model Based on Profiles Complementarity. In: Stephanidis, C., et al. HCI International 2020 – Late Breaking Papers: Cognition, Learning and Games. HCII 2020. Lecture Notes in Computer Science(), vol 12425. Springer, Cham. https://doi.org/10.1007/978-3-030-60128-7_4

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-60128-7_4

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-60127-0

  • Online ISBN: 978-3-030-60128-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics