Here you can find scientific publications of Know-Center employees

The Recommendation Dashboard: A System to Visualise and Organise Recommendations

G Tschinkel, C di Sciascio, B Mutlu, V Sabol – Proceedings of the 19th International Conference on Information Visualisa…, 2015

Recommender systems are becoming common tools supporting automatic, context-based retrieval of resources. When the number of retrieved resources grows large visual tools are required that leverage the capacity of human vision to analyse large amounts of information. We introduce a Web-based visual tool for exploring and organising recommendations retrieved from…

Towards a Recommender Engine for Personalized Visualizations

B Mutlu, E Veas, C Trattner, V Sabol – UMAP, 2015

Visual Analysis of Scientific Content

B Mutlu, V Sabol – STCSN E-LETTER ON SCIENCE 2.0, 2015

VizRec: A Two-Stage Recommender System for Personalized Visualizations

B Mutlu, E Veas, C Trattner, V Sabol – ACM IUI, 2015

Visual Recommendations for Scientific and Cultural Content

E Veas, B Mutlu, C di Sciascio, G Tschinkel, V Sabol – IVAPP 2015, 2015

Discovery and Visual Analysis of Linked Data for Humans

V Sabol, G Tschinkel, E Veas, P Hoefler, B Mutlu, M Granitzer – The Semantic Web – ISWC 2014, Lecture Notes in Compute…, 2014

Using Semantics for Interactive Visual Analysis of Linked Open Data

G Tschinkel, E Veas, B Mutlu, V Sabol – CEUR Workshop Proceedings ( Vol-1272, 2014

Providing easy to use methods for visual analysis of Linked Data is often hindered by the complexity of semantic technologies. On the other hand, semantic information inherent to Linked Data provides opportunities to support the user in interactively analysing the data. This paper provides a demonstration of an interactive, Web-based…

CODE Query Wizard and Vis Wizard: Supporting Exploration and Analysis of Linked Data

P Hoefler, B Mutlu – ERCIM News, 2014

Although the concept of Linked Data has been increasing in popularity, easy-to-use interfaces to access and make sense of the actual data are still few and far between. The CODE project's Query Wizard and Vis Wizard aim to fill this gap.

Suggesting Visualisations for Published Data

B Mutlu, P Hoefler, G Tschinkel, E Veas, V Sabol, F Stegmaier, M Granitzer – Proceedings of the 5th International Confer…, 2014

Research papers are published in various digital libraries, which deploy their own meta-models and tech- nologies to manage, query, and analyze scientific facts therein. Commonly they only consider the meta-data provided with each article, but not the contents. Hence, reaching into the contents of publications is inherently a tedious task.…

Automated Visualization Support for Linked Research Data

B Mutlu, P Hoefler, V Sabol, G Tschinkel, M Granitzer – Proceedings of i-SEMANTICS 2013, 2013

Crowdsourcing Fact Extraction from Scientific Literature

C Seifert, M Granitzer, P Hoefler, B Mutlu, V Sabol, K Schlegel, S Bayerl, F Stegmaier, S Zwicklbauer, R Kern – Proceedi…, 2013

Unleashing Semantics of Research Data

F Stegmaier, C Seifert, R Kern, P Hoefler, S Bayerl, M Granitzer, H Kosch, S Lindstaedt, B Mutlu, V Sabol, K Schlegel, S Zwicklbauer – Proceedings of the Second Workshop on Big Data Benchmarkin…, 2012

Research depends to a large degree on the availability and quality of primary research data, i.e., data generated through experi- ments 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…


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