Publikationen

Hier finden Sie von Know-Center MitarbeiterInnen verfasste wissenschaftliche Publikationen

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.
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

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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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
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.
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, 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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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

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

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

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

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

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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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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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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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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2010

Schachner W.

Wissen schafft Projektperformance

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

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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

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

Proceedings of the 2nd International Workshop on Research 2.0

CEUR Workshop Proceedings, 2010

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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

Granitzer Michael

KnowMiner - Konzeption und Entwicklung eines generischen Wissenserschließungsframeworks

Vdm Verlag Dr. Mueller (April 2008), 2008

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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

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

Journal of Universal Computer Science, Bd. 10, Nr. 6, 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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2003

Maurer H.

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

Springer Verlag, Graz, Austria, 2003

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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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2002

Personalisierung im Kontext von digitalen Bibliotheken und Wissensmanagement

Habilitationsschrift, 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

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

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

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