Recommending#-tags in twitter E Zangerle, W Gassler, G Specht Proceedings of the Workshop on Semantic Adaptive Social Web (SASWeb 2011 …, 2011 | 154 | 2011 |
HOT: A height optimized trie index for main-memory database systems R Binna, E Zangerle, M Pichl, G Specht, V Leis Proceedings of the 2018 International Conference on Management of Data, 521-534, 2018 | 117 | 2018 |
Evaluating recommender systems: survey and framework E Zangerle, C Bauer ACM Computing Surveys 55 (8), 1-38, 2022 | 116 | 2022 |
# nowplaying music dataset: Extracting listening behavior from twitter E Zangerle, M Pichl, W Gassler, G Specht Proceedings of the first international workshop on internet-scale multimedia …, 2014 | 111 | 2014 |
Overview of PAN 2021: authorship verification, profiling hate speech spreaders on twitter, and style change detection J Bevendorff, B Chulvi, GL De La Peña Sarracén, M Kestemont, ... Experimental IR Meets Multilinguality, Multimodality, and Interaction: 12th …, 2021 | 96 | 2021 |
Overview of PAN 2019: Bots and Gender Profiling, Celebrity Profiling, Cross-Domain Authorship Attribution and Style Change Detection W Daelemans, M Kestemont, E Manjavacas, M Potthast, F Rangel, ... International Conference of the Cross-Language Evaluation Forum for European …, 2019 | 96 | 2019 |
"Sorry, I was hacked": a classification of compromised twitter accounts E Zangerle, G Specht Proceedings of the 29th annual acm symposium on applied computing, 587-593, 2014 | 84 | 2014 |
Towards a context-aware music recommendation approach: What is hidden in the playlist name? M Pichl, E Zangerle, G Specht 2015 IEEE international conference on data mining workshop (ICDMW), 1360-1365, 2015 | 83 | 2015 |
On the impact of text similarity functions on hashtag recommendations in microblogging environments E Zangerle, W Gassler, G Specht Social network analysis and mining 3, 889-898, 2013 | 76 | 2013 |
Overview of the Style Change Detection Task at PAN 2020. E Zangerle, M Mayerl, M Potthast, B Stein CLEF (Working Notes) 93, 2020 | 66 | 2020 |
Hit Song Prediction: Leveraging Low-and High-Level Audio Features. E Zangerle, M Vötter, R Huber, YH Yang ISMIR, 319-326, 2019 | 54 | 2019 |
Using tag recommendations to homogenize folksonomies in microblogging environments E Zangerle, W Gassler, G Specht Social Informatics: Third International Conference, SocInfo 2011, Singapore …, 2011 | 54 | 2011 |
Personality bias of music recommendation algorithms AB Melchiorre, E Zangerle, M Schedl Proceedings of the 14th ACM Conference on Recommender Systems, 533-538, 2020 | 51 | 2020 |
Overview of pan 2020: Authorship verification, celebrity profiling, profiling fake news spreaders on twitter, and style change detection J Bevendorff, B Ghanem, A Giachanou, M Kestemont, E Manjavacas, ... Experimental IR Meets Multilinguality, Multimodality, and Interaction: 11th …, 2020 | 51 | 2020 |
Overview of PAN 2022: Authorship verification, profiling irony and stereotype spreaders, and style change detection J Bevendorff, B Chulvi, E Fersini, A Heini, M Kestemont, K Kredens, ... International Conference of the Cross-Language Evaluation Forum for European …, 2022 | 49 | 2022 |
Exploiting twitter’s collective knowledge for music recommendations E Zangerle, W Gassler, G Specht Proc. WWW Workshop:# MSM, 2012 | 44 | 2012 |
Understanding playlist creation on music streaming platforms M Pichl, E Zangerle, G Specht 2016 IEEE International Symposium on Multimedia (ISM), 475-480, 2016 | 42 | 2016 |
Support the underground: characteristics of beyond-mainstream music listeners D Kowald, P Muellner, E Zangerle, C Bauer, M Schedl, E Lex EPJ Data Science 10 (1), 14, 2021 | 40 | 2021 |
Improving context-aware music recommender systems: Beyond the pre-filtering approach M Pichl, E Zangerle, G Specht Proceedings of the 2017 ACM on International Conference on Multimedia …, 2017 | 38 | 2017 |
Combining Spotify and Twitter Data for Generating a Recent and Public Dataset for Music Recommendation. M Pichl, E Zangerle, G Specht Grundlagen von Datenbanken, 35-40, 2014 | 36 | 2014 |