@article {197,
	title = {Machine learning based work task classification},
	journal = {Journal of Digital Information Management},
	volume = {7},
	year = {2009},
	note = {Cited By (since 1996):6Export Date: 10 July 2014},
	month = {2009},
	pages = {305 - 312},
	abstract = {Increasing the productivity of a knowledge worker via intelligent applications requires the identification of a user{\textquoteright}s current work task, i.e. the current work context a user resides in. In this work we present and evaluate machine learning based work task detection methods. By viewing a work task as sequence of digital interaction patterns of mouse clicks and key strokes, we present (i) a methodology for recording those user interactions and (ii) an in-depth analysis of supervised classification models for classifying work tasks in two different scenarios: a task centric scenario and a user centric scenario. We analyze different supervised classification models, feature types and feature selection methods on a laboratory as well as a real world data set. Results show satisfiable accuracy and high user acceptance by using relatively simple types of features.},
	keywords = {Data model, Data structure, Work task classification user interaction},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-77953256434\&partnerID=40\&md5=ad1b8dc83a81694afe23a15ad90c66af},
	author = {Granitzer, M. and Rath, A.S. and Kr{\"o}ll, M. and Seifert, C. and Ipsmiller, D. and Devaurs, D. and Weber, N. and Lindstaedt, S.}
}
@article {147,
	title = {A generic framework for visualizing the news article domain and its application to real-world data},
	journal = {Journal of Digital Information Management},
	volume = {6},
	year = {2008},
	note = {Cited By (since 1996):3Export Date: 10 July 2014},
	month = {2008},
	pages = {434 - 441},
	abstract = {In this work we present APA Labs, a generic framework for visualizing the news article domain. APA Labs is a web-based platform enabling retrieval and analysis of news repositories provided by the Austrian Press Agency. APA Labs is designed as a rich internet application combined with a modular system of interactive visualizations. News articles are analyzed using domain specific named entity extraction methods combined with language specific heuristics. The proposed methods were subject to an evaluation procedure outlined in this contribution. This article illustrates the domain, the underlying concepts and implementation details. Several visualization modules are presented and an outlook on planned modules is given. Being online for around six months the community feedback as well as the easy integration of new modules shows the success of the underlying concept and the platform itself.},
	keywords = {Business process, Collaboration, Email, Interoperability, SME},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-77950335223\&partnerID=40\&md5=e07a8280eb1e93146ec05ab62b545f5a},
	author = {Lex, E. and Seifert, C. and Kienreich, W. and Granitzer, M.}
}
