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ORCIDMartin Pichl
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- affiliation: Universität Innsbruck
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2020 – today
- 2022
[j4]Robert Binna
, Eva Zangerle, Martin Pichl, Günther Specht, Viktor Leis:
Height Optimized Tries. ACM Trans. Database Syst. 47(1): 3:1-3:46 (2022)- 2021
- [j3]Martin Pichl, Eva Zangerle:
User models for multi-context-aware music recommendation. Multim. Tools Appl. 80(15): 22509-22531 (2021) - 2020
- [j2]Eva Zangerle, Martin Pichl, Markus Schedl:
User Models for Culture-Aware Music Recommendation: Fusing Acoustic and Cultural Cues. Trans. Int. Soc. Music. Inf. Retr. 3(1): 1-16 (2020)
2010 – 2019
- 2018
- [c15]Martin Pichl, Eva Zangerle:
Latent Feature Combination for Multi-Context Music Recommendation. CBMI 2018: 1-6 - [c14]Eva Zangerle, Martin Pichl:
The Many Faces of Users: Modeling Musical Preference. ISMIR 2018: 709-716 - [c13]Martin Pichl, Bernward Pichl, Eva Zangerle:
Carl: Sports Award Recommender. eCOM@SIGIR 2018 - [c12]Robert Binna, Eva Zangerle, Martin Pichl, Günther Specht, Viktor Leis:
HOT: A Height Optimized Trie Index for Main-Memory Database Systems. SIGMOD Conference 2018: 521-534 - [c11]Eva Zangerle, Martin Pichl, Markus Schedl:
Culture-Aware Music Recommendation. UMAP 2018: 357-358 - 2017
- [j1]Martin Pichl, Eva Zangerle, Günther Specht:
Understanding User-Curated Playlists on Spotify: A Machine Learning Approach. Int. J. Multim. Data Eng. Manag. 8(4): 44-59 (2017) - [c10]Martin Pichl, Eva Zangerle, Günther Specht, Markus Schedl:
Mining Culture-Specific Music Listening Behavior from Social Media Data. ISM 2017: 208-215 - [c9]Benjamin Murauer, Maximilian Mayerl, Michael Tschuggnall, Eva Zangerle, Martin Pichl, Günther Specht:
Hierarchical Multilabel Classification and Voting for Genre Classification. MediaEval 2017 - [c8]Martin Pichl, Eva Zangerle, Günther Specht:
Improving Context-Aware Music Recommender Systems: Beyond the Pre-filtering Approach. ICMR 2017: 201-208 - 2016
- [c7]Martin Pichl, Eva Zangerle, Günther Specht:
Understanding Playlist Creation on Music Streaming Platforms. ISM 2016: 475-480 - [c6]Eva Zangerle, Martin Pichl, Benedikt Hupfauf, Günther Specht:
Can Microblogs Predict Music Charts? An Analysis of the Relationship Between #Nowplaying Tweets and Music Charts. ISMIR 2016: 365-371 - [c5]Eva Zangerle, Wolfgang Gassler, Martin Pichl, Stefan Steinhauser, Günther Specht:
An Empirical Evaluation of Property Recommender Systems for Wikidata and Collaborative Knowledge Bases. OpenSym 2016: 18:1-18:8 - 2015
- [c4]Martin Pichl, Eva Zangerle, Günther Specht:
Towards a Context-Aware Music Recommendation Approach: What is Hidden in the Playlist Name? ICDM Workshops 2015: 1360-1365 - [c3]Martin Pichl, Eva Zangerle, Günther Specht:
#Nowplaying on #Spotify: Leveraging Spotify Information on Twitter for Artist Recommendations. ICWE Workshops 2015: 163-174 - 2014
- [c2]Martin Pichl, Eva Zangerle, Günther Specht:
Combining Spotify and Twitter Data for Generating a Recent and Public Dataset for Music Recommendation. Grundlagen von Datenbanken 2014: 35-40 - [c1]Eva Zangerle, Martin Pichl, Wolfgang Gassler, Günther Specht:
#nowplaying Music Dataset: Extracting Listening Behavior from Twitter. WISMM 2014: 21-26
Coauthor Index
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