From March 14th to 16th 2017 the annual ACM IUI conference takes place in Limassol, Cyprus, for the 22nd time and once again serves as a forum for the intelligent user interfaces community for reporting outstanding research and development. Eduardo Veas, Cecilia di Sciascio and Peter Hasitschka from the Know-Center will be present at the conference with one paper accepted for the main conference track, one invited paper, four workshop papers and a workshop keynote as well as with a dissertation presentation.
The paper accepted for the main conference “WikiLyzer: Interactive Information Quality Assessment in Wikipedia” reports about the toolkit WikiLyzer that was developed at Know-Center for assistance in classification of Wikipedia articles and quality flaw detection enabling users to create complex quality metrics and identify high-quality content in large digital libraries.
The invited full paper from the ACM Journal Transactions on Interactive Intelligent Systems (ACM TIIS) with the title “VizRec: Recommending Personalized Visualizations” deals with strategies to recommend suitable visualizations to users considering their preferences and how Know-Centers visual recommender VizRec addresses this challenge.
Also, the Know-Center will be very active in the IUI Workshop on Exploratory Search and Interactive Data Analytics (ESIDA 17), giving the keynote presentation and being represented by four papers:
In his keynote presentation “From Search to Discovery with Visual Exploration Tools” Eduardo Veas will outline studies on exploration of textual documents and discovery of scientific information with visual analytics interfaces. The discussion will enclose interface design and visual exploration behavior.
The paper “Visual Exploration of Large Scatter Plot Matrices by Pattern Recommendation based on Eye Tracking”, co-authored by Nelson Silva from the Know-Center, demonstrates the visual exploration process of large SPLOMs using image-based dissimilarity measures for pattern recommendation by a user study.
In the paper “Visual Exploration and Analysis of Recommender Histories: A Web-Based Approach Using WebGL” the web tool ECHO is introduced, which allows the user to visualize search results histories in order to ease re-finding and analyzing the retrieved information even with a large number of resources.
“Exploring and Summarizing Document Collections with Multiple Coordinated Views” introduces the novel system PaperViz combining an interactive web-based user interface with different visualization approaches, which supports users in extracting useful information from scientific literature. The paper discusses the tool itself as well as insights gained from a conducted usability study.
And the paper “Visual exploration of network hostile behavior” presents a graphical interface to identify hostile behavior in network logs and illustrates the workflow with the help of a design study conducted with two network security experts.
In addition to the above listed, Cecilia di Sciascio will present her thesis topic “Advanced User Interfaces and Hybrid Recommendations for Exploratory Search” at the doctoral consortium there and report on her development of an interactive intelligent tool that combines recommender systems with advanced user interfaces to assist both search tasks as well as the study of user behavior and experience.
di Sciascio, C., Strohmaier, D., Errecalde, M., & Veas, E. (2017). WikiLyzer: Interactive Information Quality Assessment in Wikipedia
Mutlu, B., Veas, E., & Trattner, C. (2016). VizRec: Recommending Personalized Visualizations. ACM Transactions on Interactive Intelligent Systems (TiiS), 6(4), 31
Shao, L., Silva,N., Eggeling, E. and Schreck, T.. Visual Exploration of Large Scatter Plot Matrices by Pattern Recommendation based on Eye Tracking
Hasitschka, P. and Sabol, V.. Visual Exploration and Analysis of Recommender Histories
di Sciascio, C., Mayr, L. and Veas, E.. Exploring and Summarizing Document Collections with Multiple Coordinated Views
Guerra, J., Catania, C. and Veas, E. Visual exploration of network hostile behavior