Publikationen

Hier finden Sie von Know-Center MitarbeiterInnen verfasste wissenschaftliche Publikationen

2019

Lassnig Markus, Stabauer Petra, Breitfuß Gert, Müller Julian M.

Erfolgreiche Konzepte und Handlungsempfehlungen für digitale Geschäftsmodellinnovationen

HMD Edition, Springer Verlag, 2019

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Zahlreiche Forschungsergebnisse im Bereich Geschäftsmodellinnovationen haben gezeigt, dass über 90 Prozent aller Geschäftsmodelle der letzten 50 Jahre aus einer Rekombination von bestehenden Konzepten entstanden sind. Grundsätzlich gilt das auch für digitale Geschäftsmodellinnovationen. Angesichts der Breite potenzieller digitaler Geschäftsmodellinnovationen wollten die Autoren wissen, welche Modellmuster in der wirtschaftlichen Praxis welche Bedeutung haben. Deshalb wurde die digitale Transformation mit neuen Geschäftsmodellen in einer empirischen Studie basierend auf qualitativen Interviews mit 68 Unternehmen untersucht. Dabei wurden sieben geeignete Geschäftsmodellmuster identifiziert, bezüglich ihres Disruptionspotenzials von evolutionär bis revolutionär klassifiziert und der Realisierungsgrad in den Unternehmen analysiert. Die stark komprimierte Conclusio lautet, dass das Thema Geschäftsmodellinnovationen durch Industrie 4.0 und digitale Transformation bei den Unternehmen angekommen ist. Es gibt jedoch sehr unterschiedliche Geschwindigkeiten in der Umsetzung und im Neuheitsgrad der Geschäftsmodellideen. Die schrittweise Weiterentwicklung von Geschäftsmodellen (evolutionär) wird von den meisten Unternehmen bevorzugt, da hier die grundsätzliche Art und Weise des Leistungsangebots bestehen bleibt. Im Gegensatz dazu gibt es aber auch Unternehmen, die bereits radikale Änderungen vornehmen, die die gesamte Geschäftslogik betreffen (revolutionäre Geschäftsmodellinnovationen). Entsprechend wird im vorliegenden Artikel ein Clustering von Geschäftsmodellinnovatoren vorgenommen – von Hesitator über Follower über Optimizer bis zu Leader in Geschäftsmodellinnovationen.
2018

Geiger Bernhard

A Short Note on the Jensen-Shannon Divergence between Simple Mixture Distributions

2018

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This short note presents results about the symmetric Jensen-Shannon divergence between two discrete mixture distributions p1 and p2. Specifically, for i=1,2, pi is the mixture of a common distribution q and a distribution p̃ i with mixture proportion λi. In general, p̃ 1≠p̃ 2 and λ1≠λ2. We provide experimental and theoretical insight to the behavior of the symmetric Jensen-Shannon divergence between p1 and p2 as the mixture proportions or the divergence between p̃ 1 and p̃ 2 change. We also provide insight into scenarios where the supports of the distributions p̃ 1, p̃ 2, and q do not coincide.
2018

Egger Peter

Smart Contracts and the Blockchain-Revolution in the area of conflict between Technology and Law

Wirtschaftskammer Österreich, MANZ'sche Verlags- und Universitätsbuchhandlung GmbH, 2018

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Similar to the creation of the internet, today the world is captivated by a new phenomenon that is considered to produce substantial impact on economic life. We are talking about the Blockchain technology, which was initially introduced as the technological backbone of the cryptocurrency Bitcoin, and is in a simplified form representing a decentralized data storage system within a peer-to-peer network. As Blockchains can be implemented in many areas of life, there are continuously emerging new ideas of utilization. One of the most promising areas of application are so-called “Smart Contracts”, which introduce new codified relationships that are both defined and automatically enforced by a code. However, fully organizing legal relationships by Smart Contracts in the near future also raises doubt on the consistency of connected processes with the law. This article examines Smart Contracts from a legal perspective, specifically explaining its place in existing Austrian contract law.
2018

Geiger Bernhard

The Global Benefits of Open Research and How It Can Change Scientific Publishing

Martyn Rittman, MDPI, 2018

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This entry for the 2018 MDPI English Writing Prize has been published as a chapter of "The Global Benefits of Open Research", edited by Martyn Rittman.
2017

Ginthör Robert, Lamb Reinhold, Koinegg Johann

Green Big Data - der Rohstoff Daten in der Energie- und Abfallwirtschaft

Green Tech Cluster GmbH, 2017

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Daten stellen den Rohstoff und die Basis für viele Unternehmen und deren künftigen wirtschaftlichen Erfolg in der Industrie dar. Diese Radar-Ausgabe knüpft inhaltlich an die veröffentlichten Radar-Ausgaben „Dienstleistungsinnovationen“ und „Digitalisierte Maschinen und Anlagen“ an und beleuchtet die technischen Möglichkeiten und zukünftigen Entwicklungen von Data-driven Business im Kontext der Green Tech Industries. Basierend auf der fortschreitenden Digitalisierung nimmt das Angebotan strukturierten und unstrukturierten Daten in den unterschiedlichen Bereichen der Wirtschaft rasant zu. In diesem Kontext gilt es sowohl interne als auch externe Daten unterschiedlichen Ursprungs zentral zu erfassen, zu validieren, miteinander zu kombinieren, auszuwerten sowie daraus neue Erkenntnisse und Anwendungen für ein Data DrivenBusiness zu generieren.
2017

Kowald Dominik

Modeling Activation Processes in Human Memory for Tag Recommendations: Using Models from Human Memory Theory to Implement Recommender Systems for Social Tagging and Microblogging Environment

Suedwestdeutscher Verlag für Hochschulschriften, TU Graz, Suedwestdeutscher Verlag für Hochschulschrifte, Graz, 2017

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Social tagging systems enable users to collaboratively assign freely chosen keywords(i.e., tags) to resources (e.g., Web links). In order to support users in finding descrip-tive tags, tag recommendation algorithms have been proposed. One issue of currentstate-of-the-art tag recommendation algorithms is that they are often designed ina purely data-driven way and thus, lack a thorough understanding of the cognitiveprocesses that play a role when people assign tags to resources. A prominent exam-ple is the activation equation of the cognitive architecture ACT-R, which formalizesactivation processes in human memory to determine if a specific memory unit (e.g.,a word or tag) will be needed in a specific context. It is the aim of this thesis toinvestigate if a cognitive-inspired approach, which models activation processes inhuman memory, can improve tag recommendations.For this, the relation between activation processes in human memory and usagepractices of tags is studied, which reveals that (i) past usage frequency, (ii) recency,and (iii) semantic context cues are important factors when people reuse tags. Basedon this, a cognitive-inspired tag recommendation approach termed BLLAC+MPrisdeveloped based on the activation equation of ACT-R. An extensive evaluation usingsix real-world folksonomy datasets shows that BLLAC+MProutperforms currentstate-of-the-art tag recommendation algorithms with respect to various evaluationmetrics. Finally, BLLAC+MPris utilized for hashtag recommendations in Twitter todemonstrate its generalizability in related areas of tag-based recommender systems.The findings of this thesis demonstrate that activation processes in human memorycan be utilized to improve not only social tag recommendations but also hashtagrecommendations. This opens up a number of possible research strands for futurework, such as the design of cognitive-inspired resource recommender systems
2017

Meixner Britta, Kaiser René, Jäger Joscha, Ooi Wei Tsang, Kosch Harald

"INTERACTIVE MEDIA: TECHNOLOGY AND EXPERIENCE" Springer Multimedia Tools and Applications (MTAP) Journal

Springer Multimedia Tools and Applications (MTAP), Springer, Springer US, 2017

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(journal special issue)
2017

Lindstaedt Stefanie , Czech Paul, Fessl Angela

Theory of Knowledge Management

A Lifecycle Approach to Knowledge Excellence in the Biopharmaceutical Industry, Nuala Calnan, Martin J Lipa, Paige E. Kane, Jose C. Menezes, CRC Press, 2017

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A Lifecycle Approach to Knowledge Excellence various industries and use cases. Through their cognitive computing-based approach, which combines the strength of man and the machine, they are setting standards within both the local and the international research community. With their expertise in the field of knowledge management they are describing the basic approaches in this chapter.
2017

Breitfuß Gert, Kaiser René, Kern Roman, Kowald Dominik, Lex Elisabeth, Pammer-Schindler Viktoria, Veas Eduardo Enrique

i-Know Workshops 2017

CEUR Workshop Proceedings for i-know 2017 conference, CEUR , CEUR, Graz, Austria, 2017

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Proceedings of the Workshop Papers of i-Know 2017, co-located with International Conference on Knowledge Technologies and Data-Driven Business 2017 (i-Know 2017), Graz, Austria, October 11-12, 2017.
2016

Atzmüller Martin, Alvin Chin, Trattner Christoph

Proceedings of the 7th International Workshop on Modeling Social Media (MSM’16) at the 25th ACM World Wide Web Conference WWW’16 conference

ACM WWW2016, ACM, Montreal, Canada, 2016

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2016

Trattner Christoph, Schäfer Hanna, Said Alan, Ludwig Bernd, Elsweiler David

Proceedings of the International Workshop on Engendering Health

10th ACM Conference on Recommender Systems, ACM, Boston, 2016

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Busy lifestyles, abundant options, lack of knowledge ... there are many reasons why people make poor decisions relating to their health. Yet these poor decisions are leading to epidemics, which represent some of the greatest challenges we face as a society today. Noncommunicable Diseases (NCDs), which include cardiovascular diseases, cancer, chronic respiratory diseases and diabetes, account for ∼60% of total deaths worldwide. These diseases share the same four behavioural risk factors: tobacco use, unhealthy diet, physical inactivity and harmful consumption of alcohol and can be prevented and sometimes even reversed with simple lifestyle changes. Eating more healthily, exercising more appropriately, sleeping and relaxing more, as well as simply being more aware of one’s state of health are all things that would lead to improved health. Yet knowing exactly what to change and how, implementing changes and maintaining changes over long time periods are all things people find challenging. These are also problems, for which we believe recommender systems can provide assistance by offering specific, tailored suggestions for behavioural change. In recent years recommender systems for health has become a popular topic within the RecSys community and a selection of empirical contributions and demo systems have been published. Efforts to date, however have been sporadic and lack coordination. We lack shared infrastructure such as datasets, appropriate cross-disciplinary knowledge, even agreed upon goals. It is our aim to use this workshop as a vehicle to:
2016

Atzmüller Martin, Chin Alvin, Trattner Christoph

Proceedings of the 7th International Workshop on Modeling Social Media

25th International World Wide Web Conference, MSM 2017, Montreal, 2016

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For the 7h International Workshop on Modeling Social Media, we aim to attract researchers from all over the world working in the field of behavioral analytics using web and social media data. Behavioral analytics is an important topic, e.g., concerning web applications as well as extensions in mobile and ubiquitous applications, for understanding user behavior. We would also like to invite researchers in the data and web mining community to lend their expertise to help to increase our understanding of the web and social media.
2015

Lacic Emanuel, Kowald Dominik, Eberhard Lukas, Trattner Christoph, Parra Denis, Marinho Leandro

Utilizing Online Social Network and Location-Based Data to Recommend Products and Categories in Online Marketplaces

Mining, Modeling, and Recommending'Things' in Social Media, MSM'2015, Springer, 2015

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Recent research has unveiled the importance of online social networks for improving the quality of recommender systems and encouraged the research community to investigate better ways of exploiting the social information for recommendations. To contribute to this sparse field of research, in this paper we exploit users’ interactions along three data sources (marketplace, social network and location-based) to assess their performance in a barely studied domain: recommending products and domains of interests (i.e., product categories) to people in an online marketplace environment. To that end we defined sets of content- and network-based user similarity features for each data source and studied them isolated using an user-based Collaborative Filtering (CF) approach and in combination via a hybrid recommender algorithm, to assess which one provides the best recommendation performance. Interestingly, in our experiments conducted on a rich dataset collected from SecondLife, a popular online virtual world, we found that recommenders relying on user similarity features obtained from the social network data clearly yielded the best results in terms of accuracy in case of predicting products, whereas the features obtained from the marketplace and location-based data sources also obtained very good results in case of predicting categories. This finding indicates that all three types of data sources are important and should be taken into account depending on the level of specialization of the recommendation task.
2015

Lindstaedt Stefanie , Ley Tobias, Sack Harald

Proceedings of the 15th International Conference on Knowledge Technologies and Data-driven Business

i-KNOW '15 15th International Conference on Knowledge Technologies and Data-Driven Business, 2015

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2015

Kowald Dominik, Seitlinger Paul, Kopeinik Simone, Ley Tobias, Trattner Christoph

Forgetting the Words but Remembering the Meaning: Modeling Forgetting in a Verbal and Semantic Tag Recommender

Mining, Modeling, and Recommending'Things' in Social Media, MSM'2015, Springer, 2015

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We assume that recommender systems are more successful,when they are based on a thorough understanding of how people processinformation. In the current paper we test this assumption in the contextof social tagging systems. Cognitive research on how people assign tagshas shown that they draw on two interconnected levels of knowledge intheir memory: on a conceptual level of semantic fields or LDA topics,and on a lexical level that turns patterns on the semantic level intowords. Another strand of tagging research reveals a strong impact oftime-dependent forgetting on users' tag choices, such that recently usedtags have a higher probability being reused than "older" tags. In thispaper, we align both strands by implementing a computational theory ofhuman memory that integrates the two-level conception and the processof forgetting in form of a tag recommender. Furthermore, we test theapproach in three large-scale social tagging datasets that are drawn fromBibSonomy, CiteULike and Flickr.As expected, our results reveal a selective effect of time: forgetting ismuch more pronounced on the lexical level of tags. Second, an extensiveevaluation based on this observation shows that a tag recommender interconnectingthe semantic and lexical level based on a theory of humancategorization and integrating time-dependent forgetting on the lexicallevel results in high accuracy predictions and outperforms other wellestablishedalgorithms, such as Collaborative Filtering, Pairwise InteractionTensor Factorization, FolkRank and two alternative time-dependentapproaches. We conclude that tag recommenders will benefit from goingbeyond the manifest level of word co-occurrences, and from includingforgetting processes on the lexical level.
2015

Silva Nelson, Eggeling Eva, Schreck Tobias, Fellner Dieter W.

Increasing Fault Tolerance in Operational Centres Using Human Sensing Technologies: Approach and Initial Results

European Project Space on Computer Vision, 2015

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2015

Kowald Dominik, Kopeinik S., Seitlinger Paul, Trattner Christoph, Ley Tobias

Refining Frequency-Based Tag Reuse Predictions by Means of Time and Semantic Context

Mining, Modeling, and Recommending'Things' in Social Media, MSM'2015, Springer, 2015

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In this paper, we introduce a tag recommendation algorithmthat mimics the way humans draw on items in their long-term memory.Based on a theory of human memory, the approach estimates a tag'sprobability being applied by a particular user as a function of usagefrequency and recency of the tag in the user's past. This probability isfurther refined by considering the inuence of the current semantic contextof the user's tagging situation. Using three real-world folksonomiesgathered from bookmarks in BibSonomy, CiteULike and Flickr, we showhow refining frequency-based estimates by considering usage recency andcontextual inuence outperforms conventional "most popular tags" approachesand another existing and very effective but less theory-driven,time-dependent recommendation mechanism.By combining our approach with a simple resource-specific frequencyanalysis, our algorithm outperforms other well-established algorithms,such as FolkRank, Pairwise Interaction Tensor Factorization and CollaborativeFiltering. We conclude that our approach provides an accurateand computationally efficient model of a user's temporal tagging behavior.We demonstrate how effective principles of recommender systemscan be designed and implemented if human memory processes are takeninto account.
2015

Kravcik Milos, Mikroyannidis Alexander, Pammer-Schindler Viktoria, Prilla Michael , Ullmann T.D.

Proceedings of the 5th Workshop on Awareness and Reflection in Technology Enhanced Learning.  In conjunction with the 10th European Conference on Technology Enhanced Learning: Design for Teaching and Learning in a Networked World

ARTEL 2015 Awareness and Reflection in Technology Enhanced Learning , 2015

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2014

Ullrich Torsten, Silva Nelson, Eggeling Eva, Fellner Dieter W.

Generative Modeling and Numerical Optimization for Energy Efficient Buildings (3)

Selected Readings in Computer Graphics , 2014

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2014

Stegmaier Florian, Seifert Christin, Kern Roman, Höfler Patrick, Bayerl Sebastian, Granitzer Michael, Kosch Harald, Lindstaedt Stefanie , Mutlu Belgin, Sabol Vedran, Schlegel Kai

Unleashing semantics of research data

Specifying Big Data Benchmarks, Springer, Berlin, Heidelberg, 2014

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Research depends to a large degree on the availability and quality of primary research data, i.e., data generated through experiments and evaluations. While the Web in general and Linked Data in particular provide a platform and the necessary technologies for sharing, managing and utilizing research data, an ecosystem supporting those tasks is still missing. The vision of the CODE project is the establishment of a sophisticated ecosystem for Linked Data. Here, the extraction of knowledge encapsulated in scientific research paper along with its public release as Linked Data serves as the major use case. Further, Visual Analytics approaches empower end users to analyse, integrate and organize data. During these tasks, specific Big Data issues are present.
2013

Ullrich Torsten, Silva Nelson, Eggeling Eva, Fellner Dieter W.

Generative Modeling and Numerical Optimization for Energy Efficient Buildings (2)

Proceedings of 2013 / OCG Energy Informatics , 2013

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2013

Ullrich Torsten, Silva Nelson, Eggeling Eva, Fellner Dieter W.

Generative Modeling and Numerical Optimization for Energy Efficient Buildings (1)

IECON 2013 , 2013

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2012

Seitlinger Christian, Schöfegger Karin, Lindstaedt Stefanie , Ley Tobias

Community-orientiertes Lernen

CSCL-Kompendium-Lehr-und Handbuch zum computerunterstützten kooperativen Lernen, Oldenburg, 2012

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2010

Wolpers Martin, Kirschner Paul A., Scheffel Maren, Lindstaedt Stefanie , Dimitrova Vania

Sustaining TEL: From Innovation to Learning and Practice

Springer Verlag, Wolpers, M., Kirschner, P. A., Scheffel, M., Lindstaedt, S. N., Dimitrova, V. , Springer, 2010

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2010

Lindstaedt Stefanie , Duval E., Ullmann T.D., Wild F., Scott P.

Proceedings of the 2nd International Workshop on Research 2.0

CEUR Workshop Proceedings, CEUR-WS, 2010

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Research2.0 is in essence a Web2.0 approach to how we do research. Research2.0 creates conversations between researchers, enables them to discuss their findings and connects them with others. Thus, Research2.0 can accelerate the diffusion of knowledge.ChallengesAs concluded during the workshop, at least four challenges are vital for future research.The first area is concerned with availability of data. Access to sanitized data and conventions on how to describe publication-related metadata provided from divergent sources are enablers for researchers to develop new views on their publications and their research area. Additional, social media data gain more and more attention. Reaching a widespread agreement about this for the field of technology-enhanced learning would be already a major step, but it is also important to focus on the next steps: what are success-critical added values driving uptake in the research community as a whole?The second area of challenges is seen in Research 2.0 practices. As technology-enhanced learning is a multidisciplinary field, practices developed in one area could be valuable for others. To extract the essence of successful multidisciplinary Research 2.0 practice though, multidimensional and longitudinal empirical work is needed. It is also an open question, if we should support practice by fostering the usage of existing tools or the development of new tools, which follow Research 2.0 principles. What makes a practice sustainable? What are the driving factors?The third challenge deals with impact. What are criteria of impact for research results (and other research artefacts) published on the Web? How can this be related to the publishing world appearing in print? Is a link equal to a citation or a download equal to a subscription? Can we develop a Research 2.0 specific position on impact measurement? This includes questions of authority, quality and re-evaluation of quality, and trust.The tension between openness and privacy spans the fourth challenge. The functionality of mash-ups often relies on the use of third-party services. What happens with the data, if this source is no longer available? What about hidden exchange of data among backend services?
2010

Schachner W.

Wissen steigert Unternehmensqualität

Wissensmanagement in der Praxis - Fokus Qualitätsmanagement, Shaker Verlag, 2010

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2010

Schachner W.

Wissen wirkt in Prozessen

Wissensmanagement in der Praxis – Fokus Prozessmanagement, Shaker Verlag, 2010

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2010

Schachner W.

Wissen schafft Projektperformance

Wissensmanagement in der Praxis - Fokus Projektmanagement, Shaker Verlag, 2010

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2010

Scheir Peter, Prettenhofer Peter, Lindstaedt Stefanie , Ghidini Chiara

An associative and adaptive network model for information retrieval in the Semantic Web

Progressive Concepts for Semantic Web Evolution: Applications and Developments, IGI Global, 2010

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While it is agreed that semantic enrichment of resources would lead to better search results, at present the low coverage of resources on the web with semantic information presents a major hurdle in realizing the vision of search on the Semantic Web. To address this problem, this chapter investigates how to improve retrieval performance in settings where resources are sparsely annotated with semantic information. Techniques from soft computing are employed to find relevant material that was not originally annotated with the concepts used in a query. The authors present an associative retrieval model for the Semantic Web and evaluate if and to which extent the use of associative retrieval techniques increases retrieval performance. In addition, the authors present recent work on adapting the network structure based on relevance feedback by the user to further improve retrieval effectiveness. The evaluation of new retrieval paradigms - such as retrieval based on technology for the Semantic Web - presents an additional challenge since no off-the-shelf test corpora exist. Hence, this chapter gives a detailed description of the approach taken to evaluate the information retrieval service the authors have built.
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

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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

Pellegrini T., Auer S., Schaffert S.

Networked Knowledge - Networked Media Integrating Knowledge Management, New Media Technologies and Semantic Systems

Studies in Computational Intelligence, Springer, 2009

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2008

Granitzer Michael, Lux M., Spaniol M.

Multimedia Semantics - The Role of Metadata

Studies in Computational Intelligence , Vol. 101, Springer, Berlin, 2008

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2008

Ulbrich Armin, Höfler Patrick, Lindstaedt Stefanie

Modellierung von Anwenderverhalten im Social Semantic Web

Social Semantic Web. Web 2.0 - Was nun?, Blumauer, A., Pellegrini, T., Springer, 2008

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Ziel dieses Kapitels ist es, gemeinsame Verwendungsszenariendes Semantic Web und des Social Web zu identifizieren und zu benennen.Dabei wird ein Teilaspekt des Themengebiets im Detail betrachtet: die Nutzungvon Services, die Beobachtungen des Verhaltens von Anwendern analysieren, umdaraus maschinell interpretierbare Informationen zu erhalten und diese als Modellezu organisieren. Es werden zunächst einige Eigenschaften und Unterscheidungsmerkmalevon Anwenderverhalten und organisierten Modellen dargestellt.Anschließend wird der mögliche wechselseitige Nutzen von Anwenderverhaltenund Modellen diskutiert. Den Abschluss bildet eine Betrachtung einiger exemplarischerSoftware-Services, die heute schon verwendet werden, um Anwenderverhaltenin Modelle überzuführen.
2008

Granitzer Michael

KnowMiner - Konzeption und Entwicklung eines generischen Wissenserschließungsframeworks

Vdm Verlag Dr. Mueller (April 2008), 2008

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2006

Lindstaedt Stefanie , Ulbrich Armin

Integration von Arbeiten und Lernen - Kompetenzentwicklung in Arbeitsprozessen

Semantic Web - Wege zur vernetzten Wissensgesellschaft, Pellegrini, T., Blumauer, A., Springer, Berlin, Germany, 2006

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2004

Maurer H.

Proceedings of the I-KNOW '04, 4th International Conference on Knowledge Management

J.UCS, Springer, Graz, Austria, 2004

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2004

Wissen richtig managen - Methoden, Technologien und Erfahrungen

Zeitschrift TELEMATIK 04/2004, Schwerpunktheft, Graz, Austria, 2004

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2004

Ley Tobias

Management Intellektuellen Kapitals: Eine sozial-interaktive Perspektive

In Wyssusek, B. (Ed.): Wissensmanagement komplex : Perspektiven und soziale Praxis, Schmidt, Berlin, 2004

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2004

Hrastnik J., Rollett H., Strohmaier M.

Heterogenes Wissen über Prozesse als Grundlage für die Geschäftsprozessverbesserung

Herausgeberband Wissenslogistik, Engelhardt, C., Hall, K., Ortner, J., Semmering, Austria, 2004

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2004

Lindstaedt Stefanie , Farmer J., Ley Tobias

Betriebliche Weiterbildung

CSCL-Kompendium - Lehr- und Handbuch für das computerunterstützte kooperative Lernen, Haake, J., Schwabe, G., Wessner, M., Oldenbourg Wissenschaftsverlag, München,Germany, 2004

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2004

Lindstaedt Stefanie , Ley Tobias, Farmer Johannes

CSCL in der betrieblichen Weiterbildung

CSCL-Kompendium-Lehr-und Handbuch für das computerunterstützte kooperative Lernen, 2004

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2004

Special Issue 'Beyond State-of-the Art Knowledge Management'

Journal of Universal Computer Science, Bd. 10, Nr. 6, 2004

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2003

Special Issue "Hot Spots in Knowledge Management"

Journal of Universal Computer Science, Bd. 6, Nr. 6, 2003

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2003

Maurer H.

Proceedings of the I-KNOW '03, 3rd International Conference on Knowledge Management

Springer Verlag, Graz, Austria, 2003

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2002

Special Issue: Hypermedia - State-of-the-Art 2002

Journal of Universal Computer Science (J.UCS), Springer, Graz Austria, 2002

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2002

Maurer H.

Proceedings of I-KNOW 02, 2nd International Conference on Knowledge Management

Springer Verlag, Graz, Austria, 2002

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2002

Personalisierung im Kontext von digitalen Bibliotheken und Wissensmanagement

Habilitationsschrift, Graz, Austria, 2002

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Lindstaedt Stefanie , Christl Conny

APOSDLE-learn@work: Firsthand Experiences and Lessons Learned

Work-Integrated Learning in Engineering, Built Environment and Technology: Diversity of Practice in Practice, IGI Global

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This chapter presents a domain-independent computational environment which supports work-integrated learning at the professional workplace. The Advanced Process-Oriented Self-Directed Learning Environment (APOSDLE) provides learning support during the execution of work tasks (instead of beforehand), within the work environment of the user (instead of within a separate learning system), and repurposes content which was not originally intended for learning (instead of relying on the expensive manual creation of learning material). Since this definition of work-integrated learning might differ from other definitions employed within this book, a short summary of the theoretical background is provided. Along the example of the company Innovation Service Network (ISN), a network of SME’s, a rich and practical description of the deployment and usage of APOSDLE is given. The chapter provides the reader with firsthand experiences and discusses efforts and lessons learned, backed up with experiences gained in two other application settings, namely EADS in France and a Chamber of Commerce and industry in Germany.

Ravenscroft Andrew, Lindstaedt Stefanie , Delgado Kloos Carlos, Hernández-Leo Davinia

21st Century Learning for 21st Century Skills

7th European Conference on Technology Enhanced Learning, EC-TEL 2012, Springer, Saarbrücken, Deutschland

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This book constitutes the refereed proceedings of the 7th European Conference on Technology Enhanced Learning, EC-TEL 2012, held in Saarbrücken, Germany, in September 2012. The 26 revised full papers presented were carefully reviewed and selected from 130 submissions. The book also includes 12 short papers, 16 demonstration papers, 11 poster papers, and 1 invited paper. Specifically, the programme and organizing structure was formed through the themes: mobile learning and context; serious and educational games; collaborative learning; organisational and workplace learning; learning analytics and retrieval; personalised and adaptive learning; learning environments; academic learning and context; and, learning facilitation by semantic means.
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