Publikationen

Hier finden Sie von Know-Center MitarbeiterInnen verfasste wissenschaftliche Publikationen

2011

Moskaliuk Johannes, Weber Nicolas, Stern Hermann, Kimmerle Joachim, Cress Ulrike, Lindstaedt Stefanie

Evaluation of social media collaboration using task-detection methods

ECTEL 2011, Palermo, Italy, 20-23 September 2011, Springer, 2011

Konferenz
Collaboration using social media is a good way of jointly constructing knowledge. This study aims at better understanding collaborative knowledge construction processes by applying innovative (micro-)task detection approaches. We take a closer look at the interactions of a user with a shared digital artifact by analyzing the captured interaction data. The goal is to identify domain-independent interaction patterns, which can serve as indicators for knowledge development (operationalized as accommodation). We designed an empirical study under laboratory conditions that used our method. The applied task detection approach identified accommodation with a rate of 77.63% without resorting to textual features. This result instantiates an improvement as compared to a previous study in which the text in focus was identified as the feature with best discriminative power. We discuss our hypothesis that our method is independent from the used knowledge domain.
2011

Weber N., Frühstück G., Ley Tobias

Unterstützung des Wissensreifungsprozesses durch Einsatz von Web 2.0 in Unternehmen

6th Conference on Professional Knowledge - From Knowledge to Action. 21. - 23. Februar 2011, Innsbruck, Austria., ISBN 978-3-88579-276-5 , Maier, R., Springer, 2011

Konferenz
2011

Weber Nicolas, Lindstaedt Stefanie

A User Centered Approach for Quality Assessment in Social Systems

KMIS, 2011

Journal
Analyzing the meaning of quality in information systems has a long tradition. As a result of the increasing amount of user generated content on the web, addressing quality is more relevant than ever. Since information is produced and consumed by different people in various contexts the perception of quality is always closely tied to the users’ situation. This work proposes an approach for assessing quality in social systems with respect to the users’ current needs.
2010

Lindstaedt Stefanie , Weber Nicolas, Schoefegger K., Nelkner T.

SIMPLE - a social interactive mashup PLE

CEUR Workshop proceedings series, Proceedings of the Third International Workshop on Mashup Personal Learning Environments (MUPPLE09), in conjunction with the 5th European Conference on Technology Enhanced Learning (EC-TEL2010), Wild, F., Kalz, M., Palmér, M., Müller, D., 2010

Konferenz
This paper presents an approach for a mashup PLE especiallydesigned for the interactive and social context of work-integratedlearning (WIL). The mashup PLE consists of a freely configurable set ofwidgets, whose functionalities are based on a framework of five activityclasses to actively support informal learning in a social environment. Wepresent an exemplary implementation of desktop widgets for each of theclasses. Based on the evaluation of the widget framework we highlightfuture research directions for designing PLEs in the context of WIL.
2009

Weber Nicolas, Ley Tobias, Lindstaedt Stefanie , Schoefegger K., Bimrose J., Brown A., Barnes S.

Knowledge Maturing in the Semantic MediaWiki: A design study in career guidance

Lecture Notes in Computer Science 5794, Cress, U., Dimitrova, V., Specht, M., Springer, 2009

Konferenz
2009

Granitzer Michael, Rath Andreas S., Kröll Mark, Ipsmiller D., Devaurs Didier, Weber Nicolas, Lindstaedt Stefanie , Seifert C.

Machine Learning based Work Task Classification

Journal of Digital Information Management, 2009

Journal
Increasing the productivity of a knowledgeworker via intelligent applications requires the identification ofa user’s current work task, i.e. the current work context a userresides in. In this work we present and evaluate machine learningbased work task detection methods. By viewing a work taskas sequence of digital interaction patterns of mouse clicks andkey strokes, we present (i) a methodology for recording thoseuser interactions and (ii) an in-depth analysis of supervised classificationmodels for classifying work tasks in two different scenarios:a task centric scenario and a user centric scenario. Weanalyze different supervised classification models, feature typesand feature selection methods on a laboratory as well as a realworld data set. Results show satisfiable accuracy and high useracceptance by using relatively simple types of features.
2009

Schoefegger K., Weber Nicolas, Lindstaedt Stefanie , Ley Tobias

KNOWLEDGE MATURING SERVICES: Supporting Knowledge Maturing in Organisational Environments

Knowledge Science, Engineering and Management, Third International Conference, KSEM 2009, Karagiannis, D., Jinpeng, Z., Springer, 2009

Konferenz
The changes in the dynamics of the economy and thecorresponding mobility and fluctuations of knowledge workers within organizationsmake continuous social learning an essential factor for an organization.Within the underlying organizational processes, KnowledgeMaturing refers to the the corresponding evolutionary process in whichknowledge objects are transformed from informal and highly contextualizedartifacts into explicitly linked and formalized learning objects.In this work, we will introduce a definition of Knowledge (Maturing)Services and will present a collection of sample services that can be dividedinto service functionality classes supporting Knowledge Maturingin content networks. Furthermore, we developed an application of thesesample services, a demonstrator which supports quality assurance withina highly content based organisational context.
2009

Ley Tobias, Lindstaedt Stefanie , Schöfegger Karin, Seitlinger Paul, Weber Nicolas, Hu Bo, Riss Uwe, Brun Roman, Hinkelmann Knut, Thönssen Barbara, Maier Ronald, Schmidt Andreas

Maturing Services Definition

2009

2008

Granitzer Michael, Kröll Mark, Seifer Christin, Rath Andreas S., Weber Nicolas, Dietzel O., Lindstaedt Stefanie

Analysis of Machine Learning Techniques for Context Extraction

Proceedings of 2008 International Conference on Digital Information Management (ICDIM08), IEEE Computer Society Press, 2008

Konferenz
’Context is key’ conveys the importance of capturing thedigital environment of a knowledge worker. Knowing theuser’s context offers various possibilities for support, likefor example enhancing information delivery or providingwork guidance. Hence, user interactions have to be aggregatedand mapped to predefined task categories. Withoutmachine learning tools, such an assignment has to be donemanually. The identification of suitable machine learningalgorithms is necessary in order to ensure accurate andtimely classification of the user’s context without inducingadditional workload.This paper provides a methodology for recording user interactionsand an analysis of supervised classification models,feature types and feature selection for automatically detectingthe current task and context of a user. Our analysisis based on a real world data set and shows the applicabilityof machine learning techniques.
2008

Rath Andreas S., Weber Nicolas, Kröll Mark, Granitzer Michael, Dietzel O., Lindstaedt Stefanie

Context-Aware Knowledge Services

Workshop on Personal Information Management (PIM2008) at the 26th Computer Human Interaction Conference (CHI2008), Florence, Italy, 2008

Konferenz
Improving the productivity of knowledge workers is anopen research challenge. Our approach is based onproviding a large variety of knowledge services which takethe current work task and information need (work context)of the knowledge worker into account. In the following wepresent the DYONIPOS application which strives toautomatically identify a user’s work task and thencontextualizes different types of knowledge servicesaccordingly. These knowledge services then provideinformation (documents, people, locations) both from theuser’s personal as well as from the organizationalenvironment. The utility and functionality is illustratedalong a real world application scenario at the Ministry ofFinance in Austria.
2007

Kröll Mark, Rath Andreas S., Weber Nicolas, Lindstaedt Stefanie , Granitzer Michael

Task Instance Classification via Graph Kernels

Mining and Learning with Graphs (MLG 07), Florenz, Italy, August 1-3, 2007, 2007

Journal
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