@article {263,
	title = {An ontology-based approach for detecting knowledge intensive tasks},
	journal = {Journal of Digital Information Management},
	volume = {9},
	year = {2011},
	note = {Cited By (since 1996):2Export Date: 10 July 2014},
	month = {2011},
	pages = {9 - 18},
	abstract = {In the context detection field, an important challenge is automatically detecting the user{\textquoteright}s task, for providing contextualized and personalized user support. Several approaches have been proposed to perform task classification, all advocating the window title as the best discriminative feature. In this paper we present a new ontology-based task detection approach, and evaluate it against previous work. We show that knowledge intensive tasks cannot be accurately classified using only the window title. We argue that our approach allows classifying such tasks better, by providing feature combinations that can adapt to the domain and the degree of freedom in task execution.},
	keywords = {Classification, Context-awareness, Task detection, User context detection, User context ontology},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-79960684788\&partnerID=40\&md5=2680764b7de9a96a3bfc50e670a65ce8},
	author = {Rath, A.S. and Devaurs, D. and Lindstaedt, S.N.}
}
