Studying the factors influencing automatic user task detection on the computer desktop

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

Volumn 6383 LNCS, Issue , 2010, Pages 292-307

  Rath, Andreas S ^a   Devaurs, Didier ^b,c   Lindstaedt, Stefanie N ^a,d  

^a KNOW CENTER   (Austria)

^b LAAS CNRS   (France)

^c UNIVERSITÉ PAUL SABATIER   (France)

^d GRAZ UNIVERSITY OF TECHNOLOGY   (Austria)

Author keywords

[No Author keywords available]

Indexed keywords

BAYES CLASSIFIER; CLASSIFICATION ACCURACY; KNOWLEDGE WORKERS; LABORATORY EXPERIMENTS; LEARNING ACTIVITY; ONTOLOGY-BASED; PERSONALIZED LEARNING; TASK DETECTION; TASK EXECUTIONS; TASK PERFORMANCE; TWO DOMAINS; WORK SUPPORT; WORK-INTEGRATED LEARNING;

CLASSIFIERS; DECISION TREES; ONTOLOGY;

INNOVATION;

EID: 78049409903     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-16020-2_20     Document Type: Conference Paper

References (29)

1. Baldauf, M., Dustdar, S., Rosenberg, F.: A survey on context-aware systems. International Journal of Ad Hoc and Ubiquitous Computing 2(4), 263-277 (2007)
2. Dey, A. K., Abowd, G. D., Salber, D.: A conceptual framework and a toolkit for supporting the rapid prototyping of context-aware applications. Human Computer Interaction 16(2), 97-166 (2001)
3. Dredze, M., Lau, T., Kushmerick, N.: Automatically classifying emails into activities. In: Proc. IUI 2006, pp. 70-77 (2006)
4. Duval, E., Hodgins, W.: A LOM research agenda. In: Proc. WWW 2003, pp. 1-9 (2003)
5. Eraut, M.: Informal learning in the workplace. Studies in Continuing Education 26(2), 247-273 (2004)
6. Fischer, G.: User modeling in human-computer interaction. User Modeling and User-Adapted Interaction 11 (1-2), 65-86 (2001)
7. Goecks, J., Shavlik, J.: Learning users' interests by unobtrusively observing their normal behavior. In: Proc. IUI 2000, pp. 129-132 (2000)
8. Granitzer, M., Kröll, M., Seifert, C., Rath, A. S., Weber, N., Dietzel, O., Lindstaedt, S. N.: Analysis of machine learning techniques for context extraction. In: Proc. ICDIM 2008, pp. 233-240 (2008)
9. Gutschmidt, A., Cap, C. H., Nerdinger, F. W.: Paving the path to automatic user task identification. In: Workshop on Common Sense Knowledge and Goal-Oriented Interfaces, IUI 2008 (2008)
10. Klieber, W., Sabol, V., Muhr, M., Kern, R., Öttl, G., Granitzer, M.: Knowledge discovery using the KnowMiner framework. In: Proc. IADIS 2009 (2009)
11. Ley, T., Ulbrich, A., Scheir, P., Lindstaedt, S. N., Kump, B., Albert, D.: Modelling competencies for supporting work-integrated learning in knowledge work. Journal of Knowledge Management 12(6), 31-47 (2008)
12. Lindstaedt, S. N., Ley, T., Scheir, P., Ulbrich, A.: Applying scruffy methods to enable workintegrated learning. European Journal of the Informatics Professional 9(3), 44-50 (2008)
13. Lindstaedt, S. N., Beham, G., Kump, B., Ley, T.: Getting to know your user - unobtrusive user model maintenance within work-integrated learning environments. In: Cress, U., Dimitrova, V., Specht, M. (eds.) EC-TEL 2009. LNCS, vol. 5794, pp. 73-87. Springer, Heidelberg (2009)
14. Lindstaedt, S. N., Scheir, P., Lokaiczyk, R., Kump, B., Beham, G., Pammer, V.: Knowledge services for work-integrated learning. In: Dillenbourg, P., Specht, M. (eds.) EC-TEL 2008. LNCS, vol. 5192, pp. 234-244. Springer, Heidelberg (2008)
15. Lokaiczyk, R., Faatz, A., Beckhaus, A., Goertz, M.: Enhancing just-in-time e-learning through machine learning on desktop context sensors. In: Kokinov, B., Richardson, D. C., Roth-Berghofer, T. R., Vieu, L. (eds.) CONTEXT 2007. LNCS (LNAI), vol. 4635, pp. 330-341. Springer, Heidelberg (2007)
16. Oliver, N., Smith, G., Thakkar, C., Surendran, A. C.: SWISH: semantic analysis of window titles and switching history. In: Proc. IUI 2006, pp. 194-201 (2006)
17. Rath, A. S.: User Interaction Context - Studying and Enhancing Automatic User Task Detection on the Computer Desktop via an Ontology-based User Interaction Context Model. Ph. D. thesis, Graz University of Technology (2010)
18. Rath, A. S., Devaurs, D., Lindstaedt, S. N.: UICO: an ontology-based user interaction context model for automatic task detection on the computer desktop. In: Workshop on Context, Information and Ontologies, ESWC 2009 (2009)
19. Schmidt, A.: Impact of context-awareness on the architecture of e-learning solutions. In: Architecture Solutions for E-Learning Systems, ch. 16, pp. 306-319. Information Science Reference, IGI Publishing (2007)
20. Schreiber, G., Akkermans, H., Anjewierden, A., Dehoog, R., Shadbolt, N., Vandevelde, W., Wielinga, B.: Knowledge Engineering and Management: The CommonKADS Methodology. The MIT Press, Cambridge (1999)
21. Shen, J., Irvine, J., Bao, X., Goodman, M., Kolibaba, S., Tran, A., Carl, F., Kirschner, B., Stumpf, S., Dietterich, T. G.: Detecting and correcting user activity switches: algorithms and interfaces. In: Proc. IUI 2009, pp. 117-126 (2009)
22. Shen, J., Li, L., Dietterich, T. G., Herlocker, J. L.: A hybrid learning system for recognizing user tasks from desktop activities and email messages. In: Proc. IUI 2006, pp. 86-92 (2006)
23. Smith, P. J.: Workplace Learning and Flexible Delivery. Review of Educational Research 73(1), 53-88 (2003)
24. Strang, T., Linnhoff-Popien, C.: A context modeling survey. In: Workshop on Advanced Context Modelling, Reasoning and Management, UbiComp 2004 (2004)
25. Ulbrich, A., Scheir, P., Lindstaedt, S. N., Görtz, M.: A context-model for supporting workintegrated learning. In: Nejdl, W., Tochtermann, K. (eds.) EC-TEL 2006. LNCS, vol. 4227, pp. 525-530. Springer, Heidelberg (2006)
26. Witten, I. H., Frank, E.: Data Mining: Practical Machine Learning Tools and Techniques, 2nd edn. Morgan Kaufmann, San Francisco (2005)
27. Wolpers, M., Najjar, J., Verbert, K., Duval, E.: Actual usage: the attention metadata approach. Educational Technology & Society 10(3), 106-121 (2007)
28. Yang, Y., Liu, X.: A re-examination of text categorization methods. In: Proc. SIGIR 1999, pp. 42-49 (1999)
29. Zhao, Y., Karypis, G., Fayyad, U.: Hierarchical clustering algorithms for document datasets. Data Mining and Knowledge Discovery 10(2), 141-168 (2005)