@inproceedings{SaidDeLucaQuercia, author = {Said, Alan and De Luca, Ernesto William and Quercia, Daniele}, title = {Report on the 4th Workshop on Context-awareness in Retrieval and Recommendation (CaRR 2014)}, series = {ACM SIGIR Forum}, volume = {48}, booktitle = {ACM SIGIR Forum}, number = {2}, publisher = {Association for Computing Machinery}, address = {New York}, issn = {0163-5840}, doi = {10.1145/2701583.2701595}, pages = {89 -- 92}, abstract = {Context-aware information is widely available in various ways and is becoming more and more important for enhancing retrieval performance and recommendation results. The current main issue to cope with is not only recommending or retrieving the most relevant items and content, but defining them ad hoc. Other relevant issues include personalizing and adapting the information and the way it is displayed to the user's current situation and interests. The workshop on Context-awareness in Retrieval and Recommendation is a forum for research on context-awareness in information retrieval, recommender systems and human computer interaction. The fourth iteration of the workshop was organized in conjunction to the 36th European Conference on Information Retrieval in Amsterdam, The Netherlands.}, subject = {Information Retrieval}, language = {en} } @inproceedings{KauerJoglekarRedietal., author = {Kauer, Tobias and Joglekar, Sagar and Redi, Miriam and Aiello, Luca Maria and Quercia, Daniele}, title = {Mapping and Visualizing Deep-Learning Urban Beautification}, series = {IEEE Computer Graphics and Applications}, volume = {38}, booktitle = {IEEE Computer Graphics and Applications}, number = {5}, publisher = {Institute of Electrical and Electronics Engineers (IEEE)}, address = {New York}, organization = {Institute of Electrical and Electronics Engineers (IEEE)}, issn = {1558-1756}, doi = {10.1109/MCG.2018.053491732}, pages = {70 -- 83}, abstract = {Information visualization has great potential to make sense of the increasing amount of data generated by complex machine-learning algorithms. We design a set of visualizations for a new deep-learning algorithm called FaceLift (goodcitylife.org/facelift). This algorithm is able to generate a beautified version of a given urban image (such as from Google Street View), and our visualizations compare pairs of original and beautified images. With those visualizations, we aim at helping practitioners understand what happened during the algorithmic beautification without requiring them to be machine-learning experts. We evaluate the effectiveness of our visualizations to do just that with a survey among practitioners. From the survey results, we derive general design guidelines on how information visualization makes complex machine-learning algorithms more understandable to a general audience.}, subject = {Visualisierung}, language = {en} } @inproceedings{SaidDeLucaQuerciaetal., author = {Said, Alan and De Luca, Ernesto William and Quercia, Daniele and B{\"o}hmer, Matthias}, title = {4th Workshop on Context-Awareness in Retrieval and Recommendation}, series = {Advances in Information Retrieval}, booktitle = {Advances in Information Retrieval}, publisher = {Springer}, address = {Cham}, isbn = {978-3-319-06028-6}, issn = {1611-3349}, doi = {10.1007/978-3-319-06028-6_100}, pages = {802 -- 805}, abstract = {Context-aware information is widely available in various ways and is becoming more and more important for enhancing retrieval performance and recommendation results. The current main issue to cope with is not only recommending or retrieving the most relevant items and content, but defining them ad hoc. Other relevant issues include personalizing and adapting the information and the way it is displayed to the user's current situation and interests. Ubiquitous computing further provides new means for capturing user feedback on items and providing information.}, subject = {Information Retrieval}, language = {en} }