@conference {DBLP:conf/semweb/LofflerWBKLSWK20,
	title = {ScholarLensViz: A Visualization Framework for Transparency in Semantic User Profiles},
	booktitle = {Proceedings of the ISWC 2020 Demos and Industry Tracks: From Novel Ideas to Industrial Practice co-located with 19th International Semantic Web Conference (ISWC 2020), Globally online, November 1-6, 2020 (UTC)},
	series = {CEUR Workshop Proceedings},
	volume = {2721},
	year = {2020},
	month = {11/2020},
	pages = {20{\textendash}25},
	publisher = {CEUR-WS.org},
	organization = {CEUR-WS.org},
	address = {[Online]},
	abstract = {Personalized applications are a two-edged sword. They are convenient and assist users by keeping the focus on relevant topics, but they are often  black boxes and users  typically do not know why certain entries appear in their profile. As transparency and provenance are essential for researchers, in this paper, we introduce ScholarLensViz, a visualization component for scholarly user profiles displaying a scholar{\textquoteright}s research competences including the provenance. It also provides visualizations to inspect the diversity of a profile and to analyze the semantic similarity of the profile entries.},
	keywords = {LOD, Provenance, Semantic User Profiles, Visualization},
	url = {http://ceur-ws.org/Vol-2721/paper485.pdf},
	attachments = {https://www.semanticsoftware.info/system/files/paper485.pdf},
	author = {Felicitas L{\"o}ffler and Valentin Wesp and Samira Babalou and Philipp Kahn and Ren{\'e} Lachmann and Bahar Sateli and Ren{\'e} Witte and Birgitta K{\"o}nig-Ries},
	editor = {Kerry L. Taylor and Rafael S. Gon{\c c}alves and Freddy L{\'e}cu{\'e} and Jun Yan}
}
