Exploiting context information for identification of relevant experts in collaborative workplace-embedded e-learning environments

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

Volumn 4753 LNCS, Issue , 2007, Pages 217-231

  Lokaiczyk, Robert ^a   Godehardt, Eicke ^b   Faatz, Andreas ^a   Goertz, Manuel ^a   Kienle, Andrea ^c   Wessner, Martin ^d   Ulbrich, Armin ^e  

^a SAP RESEARCH   (Germany)

^b FRAUNHOFER IGD   (Germany)

^c FRAUNHOFER IPSI   (Germany)

^d UNIVERSITY OF MUNICH   (Germany)

^e KNOW CENTER   (Austria)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER SUPPORTED COOPERATIVE WORK; CONTEXT FREE LANGUAGES; EXPERT SYSTEMS; MATHEMATICAL MODELS; USER INTERFACES;

COLLABORATION PARTNERS; E-LEARNING ENVIRONMENTS; KNOWLEDGE BASE;

E-LEARNING;

EID: 38349018988     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-75195-3_16     Document Type: Conference Paper

References (27)

1. Aalst, W.: Three Good reasons for Using a Petri-net-based Workflow Management System. In: Navathe, S., Wakayama, T. (eds.) Proceedings of the International Working Conference on Information and Process Integration in Enterprises (IPIC'96), Camebridge, Massachusetts, pp. 179-201 (1996)
2. Bauer, T., Leake, D.: A Research Agent Architecture for Real Time Data Collection and Analysis. In: Proceedings of the Workshop on Infrastructure for Agents, MAS, and Scalable MAS (2001)
3. Birnbaum, L., Hopp, W.J., Iravani, S., Livingston, K., Shou, B., Tirpak, T.: Task aware information access for diagnosis of manufacturing problems. In: IUI, pp. 308-310 (2005)
4. Burges, C.J.C.: A Tutorial on Support Vector Machines for Pattern Recognition. Data Mining and Knowledge Discovery 2(2), 121-167 (1998)
5. Clark, P., Boswell, R.: Rule Induction with CN2: Some Recent Improvements. Proceedings of the Fifth European Working Session on Learning 482, 151-163 (1991)
6. Domingos, P., Pazzani, M.J.: Beyond Independence: Conditions for the Optimality of the Simple Bayesian Classifier. In: International Conference on Machine Learning, pp. 105-112 (1996)
7. Fürnkranz, J., Widmer, G.: Incremental Reduced Error Pruning. In: Proceedings the Eleventh International Conference on Machine Learning, New Brunswick, NJ, pp. 70-77 (1994)
8. Han, J., Kamber, M.: Data Mining. Concepts and Techniques. Morgan Kaufmann Publishers, San Francisco (2001)
9. Horvitz, E., Breese, J., Heckerman, D., Hovel, D., Rommelse, K.: The Lumiere project: Bayesian user modeling for inferring the goals and needs of software users. In: Proceedings of the Fourteenth Conference on Uncertainty in Artificial Intelligence, Madison, WI, pp. 256-265 (1998)
10. Joachims, T.: Text Categorization with Support Vector Machines: Learning with Many Relevant Features. Proceedings of the 10th European Conference on Machine Learning, pp. 137-142 (1998)
11. Kienle, A., Menold, N., Herrmann, T.: Wissensgenese, Wissensverteilung und Wissensorganisation der der Arbeitspraxis, chapter Technische und organisatorische gestaltungsoptionen für unternehmensinterne Wissensmanagementprojekte, pp. 109-153. Westdeutscher Verlag (2003)
12. Lave, J., Wenger, E.: Situated Learning: Legitimate Peripheral Participation. Cambridge University Press, Cambridge (1991)
13. Ley, T., Lindstaedt, S.N., Albert, D.: Competency Management Using the Competence Performance Approach: Modelling, Assessment, Validation and Use. In: Sicilia, M.A. (ed.) Competencies in Organizational E-Learning, pp. 83-119. Information Science Publishing, Hershey, PA (2006)
14. Lindstaedt, S.N., Ley, T., Mayer, H.: Integrating Working and Learning with APOSDLE. In: Proceedings of the 11th Business Meeting of Forum Neue Medien, Graz, Verlag Forum Neue Medien (2005)
15. Mcdonald, D.W.: Supporting nuance in groupware design: moving from naturalistic expertise location to expertise recommendation. PhD thesis, Chair-Mark S. Ackerman (2000)
16. Mühlpfordt, M.: Dual Interaction Spaces: Integration synchroner Kommunikation und Kooperation. In: Mühlhäuser, M., Rößling, G., Steinmetz, R. (eds.) LNI, GI, vol. 87, pp. 99-110 (2006)
17. Object Management Group. OMG BPMN Final Adopted Specification (2006), http://www.omg.org/docs/dtc/06-02-01.pdf
18. Platt, J.: Fast Training of Support Vector Machines using Sequential Minimal Optimization. MIT Press, Cambridge (1998)
19. Quinlan, J.R.: Induction of Decision Trees. Machine Learning 1(1), 81-106 (1986)
20. Quinlan, J.R.: Simplifying Decision Trees. International Journal of Man-Machine Studies 27(3), 221-234 (1987)
21. Quinlan, J.R.: Learning decision tree classifiers. ACM Computing Surveys (CSUR) 28(1), 71-72 (1996)
22. Scheir, P., Hofmair, P., Granitzer, M., Lindstaedt, S.: The OntologyMapper plug-in: Supporting Semantic Annotation of Text-Documents by Classification. In: Semantic Systems From Vision to Applications - Proceedings of the SEMANTICS 2006, pp. 291-301. Österreichische Computer Gesellschaft (2006)
23. Schölkopf, B., Smola, A.J.: Learning with Kernels. MIT Press, Cambridge (2002)
24. Ulbrich, A., Scheir, P., Lindstaedt, S.N., Görtz, M.: A Context-Model for Supporting Work-Integrated Learning. In: Nejdl, W., Tochtermann, K. (eds.) EC-TEL 2006. LNCS, vol. 4227, pp. 525-530. Springer, Heidelberg (2006)
25. van Welie, M., van der Veer, G.C., Eliëns, A.: An Ontology for Task World Models. In: Markopoulos, P., Johnson, P. (eds.) Design, Specification and Verification of Interactive Systems '98, Wien, pp. 57-70. Springer, Heidelberg (1998)
26. Wasserman, S., Faust, K., Iacobucci, D.: Social Network Analysis: Methods and Applications. Structural Analysis in the Social Sciences. Cambridge University Press, Cambridge (1994)
27. Wessner, M.: Kontextuelle Kooperation in virtuellen Lernumgebungen. Eul, Lohmar (2005)