Martin Pichl

Martin Pichl, MSc.

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

2017

Bib Link

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. Dublin, Ireland, September 11-14, 2017.

Bib Link Download

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

Bib Link

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

Bib Link

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

Bib Link Download

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. ISMIR, 2016.

Bib Link Download

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

Bib Link

Martin Pichl, Eva Zangerle and Günther Specht: Towards a Context-Aware Music Recommendation Approach: What is Hidden in the Playlist Name?. In 15th IEEE International Conference on Data Mining Workshops (ICDM 2016), pages 1360-1365. IEEE, 2015.

Bib Link

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

Bib Link Download

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.

Bib Link Download

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, pages 21-26. ACM, June 2014.