Publikationen

Hier finden Sie von Know-Center MitarbeiterInnen verfasste wissenschaftliche Publikationen

2009

Lindstaedt Stefanie , Kieslinger Barbara

Science 2.0 practices in the field of technology enhanced learning

Workshop on Science 2.0 in Technology Enhanced Learning, in con-junction with European Conference on Technology Enhanced Learning: Learning in the Synergy of Multiple Disciplines, 2009

Konferenz
2009

Schmidt A., Hinkelmann K., Ley Tobias, Lindstaedt Stefanie , Maier R., Riss U.

Conceptual Foundations for a Service-oriented Knowledge and Learning Architecture: Supporting Content, Process, and Ontology Maturing

Networked Knowledge - Networked Media Integrating Knowledge Management, New Media Technologies and Semantic Systems, Studies in Computational Intelligence, Pellegrini, T., Auer, S., Tochtermann, K., Schaffert, S., Springer, 2009

Buch
Effective learning support in organizations requires a flexible and personalizedtoolset that brings together the individual and the organizational perspectiveon learning. Such toolsets need a service-oriented infrastructure of reusable knowledgeand learning services as an enabler. This contribution focuses on conceptualfoundations for such an infrastructure as it is being developed within the MATUREIP and builds on the knowledge maturing process model on the one hand, and theseeding-evolutionary growth-reseeding model on the other hand. These theories areused to derive maturing services, for which initial examples are presented.
2009

Lindstaedt Stefanie , Moerzinger R., Sorschag R. , Pammer-Schindler Viktoria, Thallinger G.

Automatic Image Annotation using Visual Conent and Folksonomies

Multimedia Tools and Applications, Springer US, 2009

Journal
Automatic image annotation is an important and challenging task, andbecomes increasingly necessary when managing large image collections. This paperdescribes techniques for automatic image annotation that take advantage of collaborativelyannotated image databases, so called visual folksonomies. Our approachapplies two techniques based on image analysis: First, classification annotates imageswith a controlled vocabulary and second tag propagation along visually similar images.The latter propagates user generated, folksonomic annotations and is thereforecapable of dealing with an unlimited vocabulary. Experiments with a pool of Flickrimages demonstrate the high accuracy and efficiency of the proposed methods in thetask of automatic image annotation. Both techniques were applied in the prototypicaltag recommender “tagr”.
2009

Lindstaedt Stefanie , Hambach S., Müsebeck P., de Hoog R., Kooken J., Musielak M.

Context and Scripts: Supporting Interactive Work-Integrated Learning

Computer Supported Collaboration Learning Practices, CSCL09, 8-13 June 2009, Rhodes, Greece, Dimitracopoulou A., O’Malley, C., Suthers D., Reimann P. , 2009

Journal
Computational support for work-integrated learning will gain more and moreattention. We understand informal self-directed work-integrated learning of knowledgeworkers as a by-product of their knowledge work activities and propose a conceptual as wellas a technical approach for supporting learning from documents and learning in interactionwith fellow knowledge workers. The paper focuses on contextualization and scripting as twomeans to specifically address the latter interaction type.
2009

Lindstaedt Stefanie , Ghidini C., Kump Barbara, Mahbub N., Pammer-Schindler Viktoria, Rospocher M., Serafini L.

MoKi: The Enterprise Modelling Wiki

The Semantic Web: Research and Applications, 6th European Semantic Web Conference, ESWC 2009, Heraklion, Crete, Greece, May 31-June 4, 2009, Proceedings, Aroyo, L., Traverso, P., Ciravegna, F., Cimiano, P., Heath, T., Hyvönen, E., Mizoguchi, R., Oren, E., Sabou, M. & Simperl, E. P. B., Springer, 2009

Konferenz
Enterprise modelling focuses on the construction of a structureddescription, the so-called enterprise model, which represents aspectsrelevant to the activity of an enterprise. Although it has becomeclearer recently that enterprise modelling is a collaborative activity, involvinga large number of people, most of the enterprise modelling toolsstill only support very limited degrees of collaboration. Within thiscontribution we describe a tool for enterprise modelling, called MoKi(MOdelling wiKI), which supports agile collaboration between all differentactors involved in the enterprise modelling activities. MoKi is basedon a Semantic Wiki and enables actors with different expertise to developan enterprise model not only using structural (formal) descriptions butalso adopting more informal and semi-formal descriptions of knowledge.
2009

Lindstaedt Stefanie , Rath Andreas S., Devaurs Didier

UICO: An Ontology-Based User Interaction Context Model for Automatic Task Detection on the Computer Desktop

Proceedings of the Context Information and Ontology (CIAO2009) workshop as part of the ESWC 2009, Gomez-Perez, J. M., Haase, P., Tilly, M., Warren, P., ACM, 2009

Konferenz
‘Understanding context is vital’ [1] and ‘context is key’ [2]signal the key interest in the context detection field. Oneimportant challenge in this area is automatically detectingthe user’s task because once it is known it is possible tosupport her better. In this paper we propose an ontologybaseduser interaction context model (UICO) that enhancesthe performance of task detection on the user’s computerdesktop. Starting from low-level contextual attention metadatacaptured from the user’s desktop, we utilize rule-based,information extraction and machine learning approaches toautomatically populate this user interaction context model.Furthermore we automatically derive relations between themodel’s entities and automatically detect the user’s task.We present evaluation results of a large-scale user study wecarried out in a knowledge-intensive business environment,which support our approach.
2009

Lindstaedt Stefanie , Christl C., Kump Barbara

Die gezielte Nutzung innerbetrieblicher Ressourcen für effektiven Kompetenztransfer

Proceedings of the Professional Training Facts conference held at Stuttgart, Germany, 11-12 November 2008 (Electronic Proceedings, CD Rom), Dworschak, B., Karapidis, A., Stuttgart: Fraunhofer-IRB-Verlag, 2009

Konferenz
Die nachhaltige Stärkung der Wettbewerbsfähigkeit von Unternehmen bedarf gezielten Wissens-und Kompetenzmanagements und strategischer Weiterentwicklungskonzepte. Der vorliegende Beitrag analysiert die gegenwärtige Situation betrieblicher Weiterbildung in kleinen und mittelständischen Unternehmen (KMU) und identifiziert eine Reihe von Herausforderungen. Computergestütztes arbeitsintegriertes Lernen wird als eine Möglichkeit vorgeschlagen, diesen Herausforderungen zu begegnen. Es werden Ergebnisse einer von uns durchgeführten Studie zu Merkmalen arbeitsintegrierten Lernens präsentiert und ein arbeitsintegriertes Lernsystem, APOSDLE, wird vorgestellt.
2009

Lindstaedt Stefanie , Rospocher M., Ghidini C., Pammer-Schindler Viktoria, Serafini L.

MoKi: the Modelling wiKi

Proceedings of the Forth Semantic Wiki Workshop (SemWiki 2009), co-located with 6th European Semantic Web Conference (ESWC 2009), CEUR Workshop Proceedings, 2009

Konferenz
Enterprise modelling focuses on the construction of a structureddescription of relevant aspects of an enterprise, the so-called enterprisemodel. Within this contribution we describe a wiki-based tool forenterprise modelling, called MoKi (Modelling wiKi). It specifically facilitatescollaboration between actors with different expertise to develop anenterprise model by using structural (formal) descriptions as well as moreinformal and semi-formal descriptions of knowledge. It also supports theintegrated development of interrelated models covering different aspectsof an enterprise.
2009

Lindstaedt Stefanie , Pammer V., Kump Barbara, Ghidini C., Rospocher M., Serafini L.

Revision support for modeling tasks, topics and skills

Proceedings of I-SEMANTICS ’09, 5th International Conference on Semantic Systems, Paschke, A., Weigand, H., Behrendt, W., Tochtermann, K., Pellegrini, T., 2009

Konferenz
Whatever purpose models are created for, they need to be evaluated inorder to ensure that they will serve their intended use. Unfortunately, model evaluationis a significant effort and no standard clear-cut evaluation methodology exists today.In this work we introduce our approach of distributing the evaluation effort over thewhole modeling process. This is achieved by providing (partly automated) feedbackon the models in different stages of development. We illustrate our approach based onthe specific goal of modeling tasks, topics and skills for the adaptive work-integratedlearning system APOSDLE.
2009

Lindstaedt Stefanie , Beham Günter, Ley Tobias, Kump Barbara

Getting to Know Your User: Unobtrusive User Model Maintenance within Work-Integrated Learning Environments

Learning in the Synergy of Multiple Disciplines: Proceedings of the 4th European Conference on Technology Enhanced Learning, ECTEL 2009, Nice, France, September/October 2009 , Cress, U., Dimitrova, V., Specht, M., Springer, 2009

Konferenz
Work-integrated learning (WIL) poses unique challenges for usermodel design: on the one hand users’ knowledge levels need to be determinedbased on their work activities – testing is not a viable option; on the other handusers do interact with a multitude of different work applications – there is nocentral learning system. This contribution introduces a user model and correspondingservices (based on SOA) geared to enable unobtrusive adaptabilitywithin WIL environments. Our hybrid user model services interpret usage datain the context of enterprise models (semantic approaches) and utilize heuristics(scruffy approaches) in order to determine knowledge levels, identify subjectmatter experts, etc. We give an overview of different types of user model services(logging, production, inference, control), provide a reference implementationwithin the APOSDLE project, and discuss early evaluation results.
2009

Rath Andreas S., Devaurs Didier, Lindstaedt Stefanie

Detecting Real User Tasks by Training on Laboratory Contextual Attention Metadata

Proceedings of Exploitation User Attention Metadata (EUAM '09) held at Informatik '09, 2009

Konferenz
Detecting the current task of a user is essential for providing her with contextualizedand personalized support, and using Contextual Attention Metadata (CAM)can help doing so. Some recent approaches propose to perform automatic user task detectionby means of task classifiers using such metadata. In this paper, we show thatgood results can be achieved by training such classifiers offline on CAM gathered inlaboratory settings. We also isolate a combination of metadata features that present asignificantly better discriminative power than classical ones.
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

Rath Andreas S., Devaurs Didier, Lindstaedt Stefanie

KnowSe: Fostering User Interaction Context Awareness

Supplementary Proceedings of the 11th European Conference on Computer Supported Cooperative Work (ECSCW '09). Demo Paper, 2009

Konferenz
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

2009

Rath Andreas S., Devaurs Didier, Lindstaedt Stefanie

Contextualized Knowledge Services for Personalized Learner Support

Fourth European Conference on Technology Enhanced Learning. Demo Paper. Lecture Notes in Computer Science. Springer, 2009

Konferenz
In this demonstration we present our KnowSe framework,developed for observing, storing, analyzing and leveraging ContextualAttention Metadata, utilizing our ontology-based user interactions contextmodel (UICO). It includes highly contextualized knowledge servicesfor supporting learners in a personalized and adaptive way, by exploitingthe learner’s user context.
2009

Lindstaedt Stefanie , de Hoog R., Aehnelt M.

APOSDLE: Contextualized Collaborative Knowledge Work Support

Supplementary Proceedings of the 11th European Conference on Computer Supported Cooperative Work, Demos, Videos, Posters, Vienna, Austria, 7 - 11 September 2009, 2009

Konferenz
This contribution shortly introduces the collaborative APOSDLE environmentfor integrated knowledge work and learning. It proposes a video presentation and thepresentation of the third APOSDLE prototype.
2009

Pammer-Schindler Viktoria, Kump Barbara, Lindstaedt Stefanie

On the feasibility of a tag-based approach for deciding which objects a picture shows: An empirical study

Semantic Multimedia. 4th International Conference on Semantic and Digital Media Technologies, SAMT 2009 Graz, Austria, December 2-4, 2009 Proceedings, Springer, 2009

Konferenz
Many online platforms allow users to describe resources withfreely chosen keywords, so called tags. The specific meaning of a tag aswell as its specific relation to the tagged resource are left open for interpretationto the user. Although human users mostly have a fair chance atinterpreting it, machines do not. An algorithmic approach for identifyingdescriptive tags however could prove useful for intelligent search for picturesand providing first-cut overviews over tagged picture repositories.In this paper we investigate the characteristics of the problem to decidewhich tags describe visible entities on a given picture. Based on a systematicuser study, we are able to discuss in detail the problems involvedfor both humans and machines when identifying descriptive tags. Furthermore,we investigate the general feasibility of developing a tag-basedalgorithm tackling this question. Finally, a concrete implementation andits evaluation are presented.
2009

Lindstaedt Stefanie , Aehnelt M., de Hoog R.

Supporting the Learning Dimension of Knowledge Work

Learning in the Synergy of Multiple Disciplines, 4th European Conference on Technology Enhanced Learning, EC-TEL 2009, Nice, France, September 29 - October 2, 2009, Cress, U., Dimitrova, V., Specht, M., 2009

Konferenz
2009

Ghidini C., Kump Barbara, Lindstaedt Stefanie , Mahbub N., Pammer-Schindler Viktoria, Rospocher M., Serafini L.

MoKi: A Collaborative Enterprise Modelling Tool (Demo and Poster)

Proceedings of the Workshop on Collaborative Construction, Management and Linking of Structured Knowledge (CK 2009) collocated with the 8th International Semantic Web Conference ISWC-2009, CEUR Workshop Proceedings, 2009

Konferenz
2009

Pammer-Schindler Viktoria, Lindstaedt Stefanie

Ontology Evaluation Through Assessment of Inferred Statements: Study of a Prototypical Implementation of an Ontology Questionnaire for OWL DL Ontologies

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

Konferenz
2009

Pammer-Schindler Viktoria, Serafini L., Lindstaedt Stefanie

Highlighting assertional effects of ontology editing activities in OWL

Proceedings of the 3rd International Workshop on Ontology Dynamics, (IWOD 2009), collocated with the 8th International Semantic Web Conference (ISWC-2009), d'Acquin, M., Antoniou, G., CEUR Workshop Proceedings, 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

Beham Günter, Lindstaedt Stefanie , Kump Barbara, Resanovic D.

Non-invasive User Modeling for Recommending Knowledgeable Persons in Work-integrated Learning

Second Stellar Alpine Rendez-Vous 2009, Workshop for Context-aware recommendation for learning, STELLAR, 2009

Konferenz
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

Kern Roman, Granitzer Michael, Lindstaedt Stefanie , Ghidini C., Scheir Peter

ARS/SD: An Associative Retrieval Service for the Semantic Desktop

Networked Knowledge - Networked Media Integrating Knowledge Management, New Media Technologies and Semantic Systems, Studies in Computational Intelligence , Pellegrini, T., Auer, S., Tochtermann, K., Schaffert, S., Springer, 2009

Buch
While it is agreed that semantic enrichment of resources wouldlead to better search results, at present the low coverage of resources onthe web with semantic information presents a major hurdle in realizing thevision of search on the Semantic Web. To address this problem we investigatehow to improve retrieval performance in a setting where resources aresparsely annotated with semantic information. We suggest employing techniquesfrom associative information retrieval to find relevant material, whichwas not originally annotated with the concepts used in a query. We presentan associative retrieval service for the Semantic Desktop and evaluate if theuse of associative retrieval techniques increases retrieval performance.Evaluation of new retrieval paradigms, as retrieval in the Semantic Web oron the Semantic Desktop, presents an additional challenge as no off-the-shelftest corpora for evaluation exist. Hence we give a detailed description of the
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