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Martin Pichl
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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
702018
# 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
662014
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
612015
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
322017
Understanding playlist creation on music streaming platforms
M Pichl, E Zangerle, G Specht
2016 IEEE International Symposium on Multimedia (ISM), 475-480, 2016
292016
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
292014
An empirical evaluation of property recommender systems for Wikidata and collaborative knowledge bases
E Zangerle, W Gassler, M Pichl, S Steinhauser, G Specht
Proceedings of the 12th International Symposium on Open Collaboration, 1-8, 2016
182016
Culture-aware music recommendation
E Zangerle, M Pichl, M Schedl
Proceedings of the 26th Conference on User Modeling, Adaptation and …, 2018
152018
Can Microblogs Predict Music Charts? An Analysis of the Relationship Between# Nowplaying Tweets and Music Charts.
E Zangerle, M Pichl, B Hupfauf, G Specht
ISMIR, 365-371, 2016
142016
Understanding user-curated playlists on spotify: A machine learning approach
M Pichl, E Zangerle, G Specht
International Journal of Multimedia Data Engineering and Management (IJMDEM …, 2017
122017
# nowplaying on# spotify: leveraging Spotify information on Twitter for artist recommendations
M Pichl, E Zangerle, G Specht
International Conference on Web Engineering, 163-174, 2015
122015
Mining culture-specific music listening behavior from social media data
M Pichl, E Zangerle, G Specht, M Schedl
2017 IEEE International Symposium on Multimedia (ISM), 208-215, 2017
112017
Latent feature combination for multi-context music recommendation
M Pichl, E Zangerle
2018 International Conference on Content-Based Multimedia Indexing (CBMI), 1-6, 2018
102018
Content-based user models: modeling the many faces of musical preference
E Zangerle, M Pichl
19th International Society for Music Information Retrieval conference (ISMIR), 2018
82018
User models for culture-aware music recommendation: fusing acoustic and cultural cues
E Zangerle, M Pichl, M Schedl
Transactions of the International Society for Music Information Retrieval 3 (1), 2020
72020
The Many Faces of Users: Modeling Musical Preference.
E Zangerle, M Pichl
ISMIR, 709-716, 2018
52018
User models for multi-context-aware music recommendation
M Pichl, E Zangerle
Multimedia Tools and Applications 80 (15), 22509-22531, 2021
42021
Hierarchical Multilabel Classification and Voting for Genre Classification.
B Murauer, M Mayerl, M Tschuggnall, E Zangerle, M Pichl, G Specht
MediaEval, 2017
42017
Multi-Context-Aware Recommender Systems: A Study on Music Rfecommendation
M Pichl
University of Innsbruck, 2018
12018
Height Optimized Tries
R Binna, E Zangerle, M Pichl, G Specht, V Leis
ACM Transactions on Database Systems (TODS) 47 (1), 1-46, 2022
2022
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