nach oben

World Wide Web

Erschienen in:

18.02.2017

Collaborative team formation using brain drain optimization: a practical and effective solution

verfasst von: Javad Basiri, Fattaneh Taghiyareh, Amineh Ghorbani

Erschienen in: World Wide Web | Ausgabe 6/2017

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config

KI-gestützte Suche

Aus

Abstract

In the area of professional social networks, collaborative team formation with its NP-hard nature, has attracted the attention of many researchers. The purpose of this study is to find a collaborative team which covers required skills and minimizes the communication cost among team members. To solve this problem, BRADO (BRAin Drain Optimization), a recently-proposed meta-heuristic swarm-based algorithm which simulates the brain drain phenomenon, has been utilized. In order to evaluate BRADO, it has been applied in extensive experiments to the DBLP and IMDb datasets. Results demonstrate the effectiveness and superiority of the BRADO algorithm in comparison with PSO, GA, ICA, RarestFirst and EnhancedSteiner algorithms. Our findings lead us to believe that the BRADO algorithm can be a promising method in the context of team formation problem.

Vorheriger Artikel Location-aware publish/subscribe index with complex boolean expressions

Nächster Artikel Community detection for emerging social networks

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

Jetzt informieren

www.linkedin.com

www.xing.com

www.networkofexperts.com

http://dblp.uni-trier.de/xml/

www.imdb.com/interfaces

http://www.ieee.org/documents/taxonomy_v101.pdf

Albert, R., Jeong, H., Barabási, A.L.: Error and attack tolerance of complex networks. Nature 406, 378–382 (2000)CrossRef

Anagnostopoulos, A., Becchetti, L., Castillo, C., Gionis, A., Leonardi, S.: Online team formation in social networks Proceedings of the 21st international conference on World Wide Web, pp 839–848. ACM (2012)

Appel, A.P., Cavalcante, V.F., Vieira, M.R., de Santana, V.F., de Paula, R.A., Tsukamoto, S.K.: Building socially connected skilled teams to accomplish complex tasks Proceedings of the 8th Workshop on Social Network Mining and Analysis, p 8. ACM (2014)

Atashpaz-Gargari, E., Lucas, C.: Imperialist Competitive Algorithm: an Algorithm for Optimization Inspired by Imperialistic Competition IEEE Congress on Evolutionary Computation, 2007. CEC 2007, pp 4661–4667. IEEE (2007)

Basiri, J., Taghiyareh, F.: An Application of the Corer Classifier on Customer Churn Prediction 2012 6th International Symposium on Telecommunications (IST), pp 867–872. IEEE (2012)

Basiri, J., Taghiyareh, F.: Introducing a socio-inspired swarm intelligence algorithm for numerical function optimization 2014 4th International eConference on Computer and Knowledge Engineering (ICCKE), pp 462–467. IEEE (2014)

Basiri, J., Taghiyareh, F., Gazani, S.: Corer: a new rule generator classifier 2010 IEEE 13th International Conference on Computational Science and Engineering (CSE), pp 64–71. IEEE (2010)

Baykasoglu, A., Dereli, T., Das, S.: Project team selection using fuzzy optimization approach. Cybern. Syst. Int. J. 38, 155–185 (2007)CrossRefMATH

Beine, M., Docquier, F., Rapoport, H.: Brain drain and human capital formation in developing countries: Winners and losers*. Econ. J. 118, 631–652 (2008)CrossRef

10.

Blum, C., Roli, A.: Metaheuristics in combinatorial optimization: Overview and conceptual comparison. ACM Comput. Surv. (CSUR) 35, 268–308 (2003)CrossRef

11.

Caseau, Y., Guillo, P.Y., Levenez, E.: A deductive and object-oriented approach to a complex scheduling problem. J. Intell. Inf. Syst. 4, 149–166 (1995)CrossRef

12.

Dorn, C., Dustdar, S.: Composing near-optimal expert teams: a trade-off between skills and connectivity OTM Confederated International Conferences “On the Move to Meaningful Internet Systems”, pp 472–489. Springer (2010)

13.

Easley, D., Kleinberg, J.: Networks, crowds, and markets: Reasoning about a highly connected world. Cambridge University Press (2010)

14.

Erd6s, P., Rényi, A.: On the evolution of random graphs. Publ. Math. Inst. Hungar. Acad. Sci 5, 17–61 (1960)

15.

Fitzpatrick, E.L., Askin, R.G.: Forming effective worker teams with multi-functional skill requirements. Comput. Ind. Eng. 48, 593–608 (2005)CrossRef

16.

Gajewar, A., Sarma, A.D.: Multi-skill collaborative teams based on densest subgraphs SDM, pp 165–176. SIAM (2012)

17.

Haupt, R.L., Haupt, S.E.: Practical genetic algorithms. Wiley (2004)

18.

Kargar, M., An, A.: Discovering top-k teams of experts with/without a leader in social networks Proceedings of the 20th ACM international conference on Information and knowledge management, pp 985–994. ACM (2011)

19.

Kargar, M., An, A., Zihayat, M.: Efficient bi-objective team formation in social networks Joint european conference on machine learning and knowledge discovery in databases, pp 483–498. Springer (2012)

20.

Kargar, M., Zihayat, M., An, A.: Finding affordable and collaborative teams from a network of experts Proceedings of the SIAM international conference on data mining (SDM), pp 587–595. SIAM (2013)

21.

Kargar, M., Zihayat, M., An, A.: Finding affordable and collaborative teams from a network of experts The 2013 SIAM International Conference on Data Mining (SDM’13), pp 587–595. SIAM (2013)

22.

Lappas, T., Liu, K., Terzi, E.: Finding a team of experts in social networks Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining, pp 467–476. ACM (2009)

23.

Lappas, T., Liu, K., Terzi, E.: A survey of algorithms and systems for expert location in social networks Social network data analytics, pp 215–241. Springer (2011)

24.

Li, C.-T., Shan, M.-K., Lin, S.-D.: On team formation with expertise query in collaborative social networks. Knowl. Inf. Syst. 42, 441–463 (2015)CrossRef

25.

Majumder, A., Datta, S., Naidu, K.: Capacitated team formation problem on social networks Proceedings of the 18th ACM SIGKDD international conference on knowledge discovery and data mining, pp 1005–1013. ACM (2012)

26.

Pashaei, K., Taghiyareh, F., Badie, K.: A recursive genetic framework for evolutionary decision-making in problems with high dynamism. Int. J. Syst. Sci. 1–17 (2014)

27.

Salehi, S., Taghiyareh, F.: Decision making improvement in social marketing strategy through dependent multi-dimensional opinion formation 2014 4th International eConference on Computer and Knowledge Engineering (ICCKE), pp 111–116. IEEE (2014)

28.

Salman, A., Ahmad, I., Al-Madani, S.: Particle swarm optimization for task assignment problem. Microprocess. Microsyst. 26, 363–371 (2002)CrossRef

29.

Sedighizadeh, D., Masehian, E.: Particle swarm optimization methods, taxonomy and applications. Int. J. Comput. Theory Eng. 1, 486–502 (2009)CrossRef

30.

Song, S.: Design of distributed database systems: an iterative genetic algorithm. J. Intell. Inf. Syst. 1–31 (2013)

31.

Talbi, E.G.: Metaheuristics: from design to implementation, vol. 74. Wiley (2009)

32.

Wang, X., Zhao, Z., Ng, W.: A comparative study of team formation in social networks International conference on database systems for advanced applications, pp 389–404. Springer (2015)

33.

Wi, H., Oh, S., Mun, J., Jung, M.: A team formation model based on knowledge and collaboration. Expert Syst. Appl. 36, 9121–9134 (2009)CrossRef

34.

Wu, L., Wu, X., Lu, A., Zhou, Z.H.: A spectral approach to detecting subtle anoMalies in graphs. J. Intell. Inf. Syst. 41, 313–337 (2013)CrossRef

35.

Yin, H., Cui, B., Huang, Y.: Finding a wise group of experts in social networks Advanced Data Mining and Applications, pp 381–394. Springer (2011)

36.

Yin, H., Cui, B., Huang, Y.: Finding a wise group of experts in social networks International Conference on Advanced Data Mining and Applications, pp 381–394. Springer (2011)

Titel: Collaborative team formation using brain drain optimization: a practical and effective solution
verfasst von: Javad Basiri
Fattaneh Taghiyareh
Amineh Ghorbani
Publikationsdatum: 18.02.2017
Verlag: Springer US
Erschienen in: World Wide Web / Ausgabe 6/2017
Print ISSN: 1386-145X
Elektronische ISSN: 1573-1413
DOI: https://doi.org/10.1007/s11280-017-0440-6

Springer Professional

Abstract

Bitte loggen Sie sich ein, um Zugang zu Ihrer Lizenz zu erhalten.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft"

Springer Professional "Wirtschaft+Technik"

Springer Professional "Technik"

Weitere Artikel der Ausgabe 6/2017

Community detection for emerging social networks

Multi-window based ensemble learning for classification of imbalanced streaming data

A query refinement framework for xml keyword search

A hybrid recommendation system considering visual information for predicting favorite restaurants

Towards better news article recommendation

Continuous range-based skyline queries in road networks

Premium Partner