Composing near-optimal expert teams: A trade-off between skills and connectivity

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 6426 LNCS, Issue PART 1, 2010, Pages 472-489

  Dorn, Christoph ^a   Dustdar, Schahram ^a  

^a VIENNA UNIVERSITY OF TECHNOLOGY   (Austria)

Author keywords

Simulated annealing; Skill connectivity tradeoff; Social network; Team formation

Indexed keywords

BUSINESS CASE; BUSINESS REQUIREMENT; EXPERT TEAMS; INTERACTION NETWORKS; INTERACTION STRUCTURES; REAL WORLD DATA; SKILL CONNECTIVITY TRADEOFF; SOCIAL NETWORKS; TEAM COMPOSITION; TEAM FORMATION; NEAR-OPTIMAL;

INTERNET; OPTIMIZATION; SIMULATED ANNEALING; SOCIAL NETWORKING (ONLINE);

SIMULATED ANNEALING; ECONOMIC AND SOCIAL EFFECTS;

EID: 78650120468     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-16934-2_35     Document Type: Conference Paper

References (24)

1. Adamic, L.A., Zhang, J., Bakshy, E., Ackerman, M.S.: Knowledge sharing and yahoo answers: everyone knows something. In: WWW 2008: Proceeding of the 17th Int. Conference on World Wide Web, pp. 665-674. ACM, New York (2008)
2. Backstrom, L., Huttenlocher, D., Kleinberg, J., Lan, X.: Group formation in large social networks: membership, growth, and evolution. In: KDD 2006: Proceedings of the 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 44-54. ACM, New York (2006)
3. Baresi, L., Bianchini, D., Antonellis, V.D., Fugini, M.G., Pernici, B., Plebani, P.: Context-aware composition of e-services. In: Benatallah, B., Shan, M.-C. (eds.) TES 2003. LNCS, vol. 2819, pp. 28-41. Springer, Heidelberg (2003)
4. Baykasoglu, A., Dereli, T., Das, S.: Project team selection using fuzzy optimization approach. Cybern. Syst. 38(2), 155-185 (2007)
5. Bird, C., Gourley, A., Devanbu, P., Gertz, M., Swaminathan, A.: Mining email social networks. In: MSR 2006: Proceedings of the 2006 Int. Workshop on Mining Software Repositories, pp. 137-143. ACM Press, New York (2006)
6. Bird, C., Pattison, D., D'Souza, R., Filkov, V., Devanbu, P.: Latent social structure in open source projects. In: SIGSOFT 2008/FSE-16: Proceedings of the 16th ACM SIGSOFT International Symposium on Foundations of software engineering, pp. 24-35. ACM, New York (2008)
7. Brin, S., Page, L.: The anatomy of a large-scale hypertextual web search engine. Computer Networks and ISDN Systems 30(1-7), 107-117 (1998); Proceedings of the Seventh International World Wide Web Conference
8. Cheatham, M., Cleereman, K.: Application of social network analysis to collaborative team formation. In: CTS 2006: Proceedings of the International Symposium on Collaborative Technologies and Systems, pp. 306-311. IEEE Computer Society, Washington (2006)
9. Colizza, V., Flammini, A., Serrano, M.A., Vespignani, A.: Detecting rich-club ordering in complex networks. Nature Physics 2, 110-115 (2006)
10. Dustdar, S., Schreiner, W.: A survey on web services composition. Int. J. Web Grid Serv. 1(1), 1-30 (2005)
11. Fitzpatrick, E.L., Askin, R.G.: Forming effective worker teams with multifunctional skill requirements. Comput. Ind. Eng. 48(3), 593-608 (2005)
12. Gaston, M.E., Simmons, J.: desJardins, M.: Adapting network structure for effi- cient team formation. In: AAMAS 2004 Workshop on Learning and Evolution in Agent Based Systems (July 2004)
13. Gómez, V., Kaltenbrunner, A., López, V.: Statistical analysis of the social network and discussion threads in slashdot. In: WWW 2008: Proceedings of the 17th Int. Conference on World Wide Web, pp. 645-654. ACM, New York (2008)
14. Haveliwala, T.: Topic-sensitive pagerank: a context-sensitive ranking algorithm for web search. IEEE Transactions on Knowledge and Data Engineering 15(4), 784-796 (2003)
15. Kirkpatrick, S., Gelatt, C.D., Vecchi, M.P.: Optimization by simulated annealing. Science 220(4598), 671-680 (1983)
16. Lappas, T., Liu, K., Terzi, E.: Finding a team of experts in social networks. In: KDD 2009: Proceedings of the 15th ACM SIGKDD Int. Conference on Knowledge Discovery and Data Mining, pp. 467-476. ACM, New York (2009)
17. Maamar, Z., Benslimane, D., Thiran, P., Ghedira, C., Dustdar, S., Sattanathan, S.: Towards a context-based multi-type policy approach for web services composition. Data Knowl. Eng. 62(2), 327-351 (2007)
18. McAuley, J.J., da Fontoura Costa, L., Caetano, T.S.: Rich-club phenomenon across complex network hierarchies. Applied Physics Letters 91(8), 084103 (2007)
19. Quitadamo, R., Zambonelli, F., Cabri, G.: The service ecosystem: Dynamic selfaggregation of pervasive communication services. In: First International Workshop on Software Engineering for Pervasive Computing Applications, Systems, and Environments, SEPCASE 2007, pp. 1-10 (May 2007)
20. Schall, D.: Human Interactions in Mixed Systems - Architecture, Protocols, and Algorithms. PhD Thesis, Vienna University of Technology, Karlsplatz 13, 1040 Vienna, Austria (2009)
21. Skopik, F., Schall, D., Dustdar, S.: Modeling and mining of dynamic trust in complex service-oriented systems. Information Systems Journal 35(7), 735-757 (2010)
22. Skopik, F., Truong, H.L., Dustdar, S.: Trust and reputation mining in professional virtual communities. In: Gaedke, M., Grossniklaus, M., Díaz, O. (eds.) ICWE 2009. LNCS, vol. 5648, pp. 76-90. Springer, Heidelberg (2009)
23. Wi, H., Oh, S., Mun, J., Jung, M.: A team formation model based on knowledge and collaboration. Expert Syst. Appl. 36(5), 9121-9134 (2009)
24. Yang, Y., Mahon, F., Williams, M.H., Pfeifer, T.: Context-aware dynamic personalised service re-composition in a pervasive service environment. In: Ma, J., Jin, H., Yang, L.T., Tsai, J.J.-P. (eds.) UIC 2006. LNCS, vol. 4159, pp. 724-735. Springer, Heidelberg (2006)