Martin Pichl

Martin Pichl, PhD

Tel: +43 512 507 53320
Fax
+43 512 507 53059
Office
ICT building, 2nd floor, room 3S01

Martin Pichl is PhD student and university assistant in the DBIS-Group. He is focusing on (music) recommender systems but is generally interested in data science, machine learning and information retrieval.

Publications

2018

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Martin Pichl and Eva Zangerle: Latent Feature Combination for Multi-Context Music Recommendation. In 2018 International Conference on Content-Based Multimedia Indexing (CBMI), pages 1-6. 2018

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Eva Zangerle and Martin Pichl: Content-based User Models: Modeling the Many Faces of Musical Preference. In Proceedings of the 19th International Society for Music Information Retrieval Conference 2018 (ISMIR 2018), pages 709-716. 2018

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Martin Pichl, Bernward Pichl and Eva Zangerle: Carl: Sports Award Recommender. In The SIGIR 2018 Workshop On eCommerce co-located with the 41st International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2018), Ann Arbor, Michigan, USA, July 12, 2018., vol. 2319. CEUR-WS.org, 2018

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Eva Zangerle, Martin Pichl and Markus Schedl: Culture-Aware Music Recommendation. In Proceedings of the 26th Conference on User Modeling, Adaptation and Personalization (UMAP 2018), pages 357-358. ACM, 2018

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Robert Binna, Eva Zangerle, Martin Pichl, Günther Specht and Viktor Leis: HOT: A Height Optimized Trie Index for Main-Memory Database Systems. In Proceedings of the 2018 International Conference on Management of Data (SIGMOD 2018), pages 521-534. ACM, 2018

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Martin Pichl: Multi-Context-Aware Recommender Systems: A Study on Music Recommendation. PhD thesis, University of Innsbruck, Department of Computer Science, 2018.

2017

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Martin Pichl, Eva Zangerle, Günther Specht and Markus Schedl: Mining Culture-Specific Music Listening Behavior from Social Media Data. In Proceedings of the IEEE International Symposium on Multimedia (ISM 2017), Taichung, Taiwan, December 11-13, 2017, pages 208-215. IEEE Computer Society, 2017

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Benjamin Murauer, Maximilian Mayerl, Michael Tschuggnall, Eva Zangerle, Martin Pichl and Günther Specht: Hierarchical Multilabel Classification and Voting for Genre Classification. In CEURS Working Notes Proceedings of the MediaEval 2017 Workshop. CEUR-WS.org, 2017

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Martin Pichl, Eva Zangerle and Günther Specht: Improving Context-Aware Music Recommender Systems: Beyond the Pre-filtering Approach. In Proceedings of the 2017 ACM International Conference on Multimedia Retrieval (ICMR 2017), pages 201-208. ACM, 2017

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Martin Pichl, Eva Zangerle and Günther Specht: Understanding User-curated Playlists on Spotify: A Machine Learning Approach. In International Journal of Multimedia Data Engineering and Management (IJMDEM), vol. 8, no. 4. 2017

2016

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Martin Pichl, Eva Zangerle and Günther Specht: Understanding Playlist Creation on Music Streaming Platforms. In Proceedings of the IEEE Symposium on Multimedia (ISM), pages 475-480. IEEE, 2016

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Eva Zangerle, Martin Pichl, Benedikt Hupfauf and Günther Specht: Can Microblogs Predict Music Charts? An Analysis of the Relationship Between #Nowplaying Tweets and Music Charts. In Proceedings of the 17th International Society for Music Information Retrieval Conference (ISMIR 2016), New York City, United States, August 7-11, 2016, pages 365-371.

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Eva Zangerle, Wolfgang Gassler, Martin Pichl, Stefan Steinhauser and Günther Specht: An Empirical Evaluation of Property Recommender Systems for Wikidata and Collaborative Knowledge Bases. In Proceedings of the 12th International Symposium on Open Collaboration (OpenSym 2016), Berlin, Germany, August 17-19, 2016, pages 18:1-18:8. ACM, 2016.

2015

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Martin Pichl, Eva Zangerle and Günther Specht: Towards a Context-Aware Music Recommendation Approach: What is Hidden in the Playlist Name?. In Proceedings of 15th IEEE International Conference on Data Mining Workshops (ICDM 2015), pages 1360-1365. IEEE, 2015.

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Martin Pichl, Eva Zangerle and Günther Specht: #nowplaying on #Spotify: Leveraging Spotify Information on Twitter for Artist Recommendations. In Current Trends in Web Engineering, 15th International Conference, ICWE 2015 Workshops (Revised Selected Papers), pages 163-174. Springer, 2015.

2014

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Martin Pichl, Eva Zangerle and Günther Specht: Combining Spotify and Twitter Data for Generating a Recent and Public Dataset for Music Recommendation. In Proceedings of the 26nd Workshop Grundlagen von Datenbanken (GvDB 2014), Ritten, Italy, vol. 1313, pages 35-40. CEUR-WS.org, Oct. 2014.

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Eva Zangerle, Martin Pichl, Wolfgang Gassler and Günther Specht: #nowplaying Music Dataset: Extracting Listening Behavior from Twitter. In Proceedings of the 1st ACM International Workshop on Internet-Scale Multimedia Management (WISMM '14), pages 21-26. ACM, June 2014.