default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDMarkus Schedl
Person information
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2025
[i43]Andreas Peintner, Marta Moscati, Emilia Parada-Cabaleiro, Markus Schedl, Eva Zangerle:
Unsupervised Graph Embeddings for Session-based Recommendation with Item Features. CoRR abs/2502.13763 (2025)- 2024
- [j47]Yashar Deldjoo
, Markus Schedl, Peter Knees:
Content-driven music recommendation: Evolution, state of the art, and challenges. Comput. Sci. Rev. 51: 100618 (2024) - [j46]Deepak Kumar, Tessa Grosz, Navid Rekabsaz, Elisabeth Greif, Markus Schedl:
Fairness of recommender systems in the recruitment domain: an analysis from technical and legal perspectives. Frontiers Big Data 6 (2024) - [j45]Peter Müllner, Elisabeth Lex, Markus Schedl, Dominik Kowald:
Differential privacy in collaborative filtering recommender systems: a review. Frontiers Big Data 6 (2024) - [c220]Gustavo Escobedo, Christian Ganhör, Stefan Brandl, Mirjam Augstein, Markus Schedl:
Simultaneous Unlearning of Multiple Protected User Attributes From Variational Autoencoder Recommenders Using Adversarial Training. BIAS 2024: 91-102 - [c219]Shahed Masoudian, Cornelia Volaucnik, Markus Schedl, Navid Rekabsaz:
Effective Controllable Bias Mitigation for Classification and Retrieval using Gate Adapters. EACL (1) 2024: 2434-2453 - [c218]Linda Ratz, Markus Schedl, Simone Kopeinik, Navid Rekabsaz:
Measuring Bias in Search Results Through Retrieval List Comparison. ECIR (5) 2024: 20-34 - [c217]Peter Müllner, Elisabeth Lex, Markus Schedl, Dominik Kowald:
The Impact of Differential Privacy on Recommendation Accuracy and Popularity Bias. ECIR (4) 2024: 466-482 - [c216]Shahed Masoudian, Markus Frohmann, Navid Rekabsaz, Markus Schedl:
Unlabeled Debiasing in Downstream Tasks via Class-wise Low Variance Regularization. EMNLP 2024: 10932-10938 - [c215]Markus Frohmann, Igor Sterner, Ivan Vulic, Benjamin Minixhofer, Markus Schedl:
Segment Any Text: A Universal Approach for Robust, Efficient and Adaptable Sentence Segmentation. EMNLP 2024: 11908-11941 - [c214]Markus Schedl, Oleg Lesota, Shahed Masoudian:
The Importance of Cognitive Biases in the Recommendation Ecosystem: Evidence of Feature-Positive Effect, Ikea Effect, and Cultural Homophily. IntRS@RecSys 2024: 113-123 - [c213]Muhammad Saad Saeed, Shah Nawaz, Marta Moscati, Rohan Kumar Das, Muhammad Salman Tahir, Muhammad Zaigham Zaheer, Muhammad Irzam Liaqat, Muhammad Haris Khan, Karthik Nandakumar, Muhammad Haroon Yousaf, Markus Schedl:
A Synopsis of FAME 2024 Challenge: Associating Faces with Voices in Multilingual Environments. ACM Multimedia 2024: 11333-11334 - [c212]Alessandro B. Melchiorre, Shahed Masoudian, Deepak Kumar, Markus Schedl:
Modular Debiasing of Latent User Representations in Prototype-Based Recommender Systems. ECML/PKDD (1) 2024: 56-72 - [c211]Gustavo Escobedo, Marta Moscati, Peter Muellner, Simone Kopeinik, Dominik Kowald, Elisabeth Lex, Markus Schedl:
Making Alice Appear Like Bob: A Probabilistic Preference Obfuscation Method For Implicit Feedback Recommendation Models. ECML/PKDD (7) 2024: 349-365 - [c210]Christian Ganhör, Marta Moscati, Anna Hausberger, Shah Nawaz, Markus Schedl:
A Multimodal Single-Branch Embedding Network for Recommendation in Cold-Start and Missing Modality Scenarios. RecSys 2024: 380-390 - [c209]Oleg Lesota, Jonas Geiger, Max Walder, Dominik Kowald, Markus Schedl:
Oh, Behave! Country Representation Dynamics Created by Feedback Loops in Music Recommender Systems. RecSys 2024: 1022-1027 - [c208]Marta Moscati, Hannah Strauß, Peer-Ole Jacobsen, Andreas Peintner, Eva Zangerle, Marcel Zentner, Markus Schedl:
Emotion-Based Music Recommendation from Quality Annotations and Large-Scale User-Generated Tags. UMAP 2024: 159-164 - [c207]Markus Schedl, Vito Walter Anelli, Elisabeth Lex:
Trustworthy User Modeling and Recommendation From Technical and Regulatory Perspectives. UMAP (Adjunct Publication) 2024 - [c206]Markus Schedl, Marta Moscati, Bruno Sguerra, Romain Hennequin, Elisabeth Lex:
Psychology-informed Information Access Systems Workshop. WSDM 2024: 1216-1217 - [d3]Peter Müllner, Elisabeth Lex, Markus Schedl, Dominik Kowald:
LFM User Groups Implicit Feedback. Zenodo, 2024
- [i42]Peter Müllner, Elisabeth Lex, Markus Schedl, Dominik Kowald:
The Impact of Differential Privacy on Recommendation Accuracy and Popularity Bias. CoRR abs/2401.03883 (2024) - [i41]Shahed Masoudian, Cornelia Volaucnik, Markus Schedl, Navid Rekabsaz:
Effective Controllable Bias Mitigation for Classification and Retrieval using Gate Adapters. CoRR abs/2401.16457 (2024) - [i40]Muhammad Saad Saeed, Shah Nawaz, Muhammad Salman Tahir, Rohan Kumar Das, Muhammad Zaigham Zaheer, Marta Moscati, Markus Schedl, Muhammad Haris Khan, Karthik Nandakumar, Muhammad Haroon Yousaf:
Face-voice Association in Multilingual Environments (FAME) Challenge 2024 Evaluation Plan. CoRR abs/2404.09342 (2024) - [i39]Gustavo Escobedo, Marta Moscati, Peter Muellner, Simone Kopeinik, Dominik Kowald, Elisabeth Lex, Markus Schedl:
Making Alice Appear Like Bob: A Probabilistic Preference Obfuscation Method For Implicit Feedback Recommendation Models. CoRR abs/2406.11505 (2024) - [i38]Markus Frohmann, Igor Sterner, Ivan Vulic, Benjamin Minixhofer, Markus Schedl:
Segment Any Text: A Universal Approach for Robust, Efficient and Adaptable Sentence Segmentation. CoRR abs/2406.16678 (2024) - [i37]Muhammad Irzam Liaqat, Shah Nawaz, Muhammad Zaigham Zaheer, Muhammad Saad Saeed, Hassan Sajjad, Tom De Schepper, Karthik Nandakumar, Muhammad Haris Khan, Markus Schedl:
Chameleon: Images Are What You Need For Multimodal Learning Robust To Missing Modalities. CoRR abs/2407.16243 (2024) - [i36]Muhammad Saad Saeed, Shah Nawaz, Muhammad Zaigham Zaheer, Muhammad Haris Khan, Karthik Nandakumar, Muhammad Haroon Yousaf, Hassan Sajjad, Tom De Schepper, Markus Schedl:
Modality Invariant Multimodal Learning to Handle Missing Modalities: A Single-Branch Approach. CoRR abs/2408.07445 (2024) - [i35]Oleg Lesota, Jonas Geiger, Max Walder, Dominik Kowald, Markus Schedl:
Oh, Behave! Country Representation Dynamics Created by Feedback Loops in Music Recommender Systems. CoRR abs/2408.11565 (2024) - [i34]Markus Schedl, Oleg Lesota, Stefan Brandl, Mohammad Lotfi, Gustavo Junior Escobedo Ticona, Shahed Masoudian:
The Importance of Cognitive Biases in the Recommendation Ecosystem. CoRR abs/2408.12492 (2024) - [i33]Christian Ganhör, Marta Moscati, Anna Hausberger, Shah Nawaz, Markus Schedl:
A Multimodal Single-Branch Embedding Network for Recommendation in Cold-Start and Missing Modality Scenarios. CoRR abs/2409.17864 (2024) - [i32]Shahed Masoudian, Markus Frohmann, Navid Rekabsaz, Markus Schedl:
Unlabeled Debiasing in Downstream Tasks via Class-wise Low Variance Regularization. CoRR abs/2409.19541 (2024) - [i31]Gustavo Escobedo, Christian Ganhör, Stefan Brandl, Mirjam Augstein, Markus Schedl:
Simultaneous Unlearning of Multiple Protected User Attributes From Variational Autoencoder Recommenders Using Adversarial Training. CoRR abs/2410.20965 (2024) - 2023
- [j44]Markus Frohmann, Manuel Karner, Said Khudoyan, Robert Wagner, Markus Schedl:
Predicting the Price of Bitcoin Using Sentiment-Enriched Time Series Forecasting. Big Data Cogn. Comput. 7(3): 137 (2023) - [j43]Alessandro B. Melchiorre, David Penz, Christian Ganhör, Oleg Lesota, Vasco Fragoso, Florian Fritzl, Emilia Parada-Cabaleiro, Franz Schubert, Markus Schedl:
Emotion-aware music tower blocks (EmoMTB ): an intelligent audiovisual interface for music discovery and recommendation. Int. J. Multim. Inf. Retr. 12(1): 13 (2023) - [j42]Tommaso Di Noia, In-Young Ko, Markus Schedl:
Introduction to the ICWE 2022 Special Issue. J. Web Eng. 22(1): v-viii (2023) - [j41]Peter Müllner, Elisabeth Lex, Markus Schedl, Dominik Kowald:
ReuseKNN: Neighborhood Reuse for Differentially Private KNN-Based Recommendations. ACM Trans. Intell. Syst. Technol. 14(5): 80:1-80:29 (2023) - [c205]Lukas Hauzenberger, Shahed Masoudian, Deepak Kumar, Markus Schedl, Navid Rekabsaz:
Modular and On-demand Bias Mitigation with Attribute-Removal Subnetworks. ACL (Findings) 2023: 6192-6214 - [c204]Dominik Kowald, Gregor Mayr, Markus Schedl, Elisabeth Lex:
A Study on Accuracy, Miscalibration, and Popularity Bias in Recommendations. BIAS 2023: 1-16 - [c203]Simone Kopeinik, Martina Mara, Linda Ratz, Klara Krieg, Markus Schedl, Navid Rekabsaz:
Show me a "Male Nurse"! How Gender Bias is Reflected in the Query Formulation of Search Engine Users. CHI 2023: 137:1-137:15 - [c202]Bruce Ferwerda, Eveline Ingesson, Michaela Berndl, Markus Schedl:
I Don't Care How Popular You Are! Investigating Popularity Bias in Music Recommendations from a User's Perspective. CHIIR 2023: 357-361 - [c201]Klara Krieg, Emilia Parada-Cabaleiro, Gertraud Medicus, Oleg Lesota, Markus Schedl, Navid Rekabsaz:
Grep-BiasIR: A Dataset for Investigating Gender Representation Bias in Information Retrieval Results. CHIIR 2023: 444-448 - [c200]Deepak Kumar, Oleg Lesota, George Zerveas, Daniel Cohen, Carsten Eickhoff, Markus Schedl, Navid Rekabsaz:
Parameter-efficient Modularised Bias Mitigation via AdapterFusion. EACL 2023: 2730-2743 - [c199]Shahed Masoudian, Khaled Koutini, Markus Schedl, Gerhard Widmer, Navid Rekabsaz:
Domain Information Control at Inference Time for Acoustic Scene Classification. EUSIPCO 2023: 181-185 - [c198]Deepak Kumar, Tessa Grosz, Elisabeth Greif, Navid Rekabsaz, Markus Schedl:
Identifying Words in Job Advertisements Responsible for Gender Bias in Candidate Ranking Systems via Counterfactual Learning. HR@RecSys 2023 - [c197]Raisa Romanov Geleta, Klaus Eckelt, Emilia Parada-Cabaleiro, Markus Schedl:
Exploring Intensities of Hate Speech on Social Media: A Case Study on Explaining Multilingual Models with XAI. LDK 2023: 532-537 - [c196]Marta Moscati, Yashar Deldjoo, Giulio Davide Carparelli, Markus Schedl:
Multiobjective Hyperparameter Optimization of Recommender Systems. Perspectives@RecSys 2023 - [c195]Marta Moscati, Christian Wallmann, Markus Reiter-Haas, Dominik Kowald, Elisabeth Lex, Markus Schedl:
Integrating the ACT-R Framework with Collaborative Filtering for Explainable Sequential Music Recommendation. RecSys 2023: 840-847 - [c194]Markus Schedl, Vito Walter Anelli, Elisabeth Lex:
Trustworthy Recommender Systems: Technical, Ethical, Legal, and Regulatory Perspectives. RecSys 2023: 1288-1290 - [c193]Oleg Lesota, Gustavo Escobedo, Yashar Deldjoo, Bruce Ferwerda, Simone Kopeinik, Elisabeth Lex, Navid Rekabsaz, Markus Schedl:
Computational Versus Perceived Popularity Miscalibration in Recommender Systems. SIGIR 2023: 1889-1893 - [c192]Veronika Arefieva, Roman Egger, Michael Schrefl, Markus Schedl:
Travel Bird: A Personalized Destination Recommender with TourBERT and Airbnb Experiences. WSDM 2023: 1164-1167 - [c191]Markus Schedl, Emilia Gómez, Elisabeth Lex:
Trustworthy Algorithmic Ranking Systems. WSDM 2023: 1240-1243 - [d2]Marta Moscati, Christian Wallmann, Markus Reiter-Haas, Dominik Kowald, Elisabeth Lex, Markus Schedl:
Files for Integrating the ACT-R Framework with Collaborative Filtering for Explainable Sequential Music Recommendation. Zenodo, 2023 - [i30]Deepak Kumar, Oleg Lesota, George Zerveas, Daniel Cohen, Carsten Eickhoff, Markus Schedl, Navid Rekabsaz:
Parameter-efficient Modularised Bias Mitigation via AdapterFusion. CoRR abs/2302.06321 (2023) - [i29]Dominik Kowald, Gregor Mayr, Markus Schedl, Elisabeth Lex:
A Study on Accuracy, Miscalibration, and Popularity Bias in Recommendations. CoRR abs/2303.00400 (2023) - [i28]Shahed Masoudian, Khaled Koutini, Markus Schedl, Gerhard Widmer, Navid Rekabsaz:
Domain Information Control at Inference Time for Acoustic Scene Classification. CoRR abs/2306.08010 (2023) - 2022
- [j40]Darius Afchar, Alessandro B. Melchiorre, Markus Schedl, Romain Hennequin, Elena V. Epure, Manuel Moussallam:
Explainability in Music Recommender Systems. AI Mag. 43(2): 190-208 (2022) - [j39]Tommaso Di Noia, Nava Tintarev, Panagiota Fatourou, Markus Schedl:
Recommender systems under European AI regulations. Commun. ACM 65(4): 69-73 (2022) - [j38]Mihai Gabriel Constantin, Liviu-Daniel Stefan, Bogdan Ionescu, Claire-Hélène Demarty, Mats Sjöberg, Markus Schedl, Guillaume Gravier:
Affect in Multimedia: Benchmarking Violent Scenes Detection. IEEE Trans. Affect. Comput. 13(1): 347-366 (2022) - [c190]Klara Krieg, Emilia Parada-Cabaleiro, Markus Schedl, Navid Rekabsaz:
Do Perceived Gender Biases in Retrieval Results Affect Relevance Judgements? BIAS 2022: 104-116 - [c189]Markus Schedl, Stefan Brandl, Oleg Lesota, Emilia Parada-Cabaleiro, David Penz, Navid Rekabsaz:
LFM-2b: A Dataset of Enriched Music Listening Events for Recommender Systems Research and Fairness Analysis. CHIIR 2022: 337-341 - [c188]Elisabeth Lex, Markus Schedl:
Psychology-informed Recommender Systems: A Human-Centric Perspective on Recommender Systems. CHIIR 2022: 367-368 - [c187]Marta Moscati, Emilia Parada-Cabaleiro, Yashar Deldjoo, Eva Zangerle, Markus Schedl:
Music4All-Onion - A Large-Scale Multi-faceted Content-Centric Music Recommendation Dataset. CIKM 2022: 4339-4343 - [c186]Oleg Lesota, Emilia Parada-Cabaleiro, Stefan Brandl, Elisabeth Lex, Navid Rekabsaz, Markus Schedl:
Traces of Globalization in Online Music Consumption Patterns and Results of Recommendation Algorithms. ISMIR 2022: 291-297 - [c185]Maximilian Mayerl, Stefan Brandl, Günther Specht, Markus Schedl, Eva Zangerle:
Verse versus Chorus: Structure-aware Feature Extraction for Lyrics-based Genre Recognition. ISMIR 2022: 884-890 - [c184]Alessandro B. Melchiorre, David Penz, Christian Ganhör, Oleg Lesota, Vasco Fragoso, Florian Friztl, Emilia Parada-Cabaleiro, Franz Schubert, Markus Schedl:
EmoMTB: Emotion-aware Music Tower Blocks. ICMR 2022: 206-210 - [c183]Oleg Lesota, Stefan Brandl, Matthias Wenzel, Alessandro B. Melchiorre, Elisabeth Lex, Navid Rekabsaz, Markus Schedl:
Exploring Cross-group Discrepancies in Calibrated Popularity for Accuracy/Fairness Trade-off Optimization. MORS@RecSys 2022 - [c182]Alessandro B. Melchiorre, Navid Rekabsaz, Christian Ganhör, Markus Schedl:
ProtoMF: Prototype-based Matrix Factorization for Effective and Explainable Recommendations. RecSys 2022: 246-256 - [c181]Elisabeth Lex, Markus Schedl:
Psychology-informed Recommender Systems Tutorial. RecSys 2022: 714-717 - [c180]Christian Ganhör, David Penz, Navid Rekabsaz, Oleg Lesota, Markus Schedl:
Unlearning Protected User Attributes in Recommendations with Adversarial Training. SIGIR 2022: 2142-2147 - [c179]Markus Schedl, Emilia Gómez, Elisabeth Lex:
Retrieval and Recommendation Systems at the Crossroads of Artificial Intelligence, Ethics, and Regulation. SIGIR 2022: 3420-3424 - [c178]Markus Schedl, Navid Rekabsaz, Elisabeth Lex, Tessa Grosz, Elisabeth Greif:
Multiperspective and Multidisciplinary Treatment of Fairness in Recommender Systems Research. UMAP (Adjunct Publication) 2022: 90-94 - [c177]Riccardo Tommasini, Senjuti Basu Roy, Xuan Wang, Hongwei Wang, Heng Ji, Jiawei Han, Preslav Nakov, Giovanni Da San Martino, Firoj Alam, Markus Schedl, Elisabeth Lex, Akash Bharadwaj, Graham Cormode, Milan Dojchinovski, Jan Forberg, Johannes Frey, Pieter Bonte, Marco Balduini, Matteo Belcao, Emanuele Della Valle, Junliang Yu, Hongzhi Yin, Tong Chen, Haochen Liu, Yiqi Wang, Wenqi Fan, Xiaorui Liu, Jamell Dacon, Lingjuan Lye, Jiliang Tang, Aristides Gionis, Stefan Neumann, Bruno Ordozgoiti, Simon Razniewski, Hiba Arnaout, Shrestha Ghosh, Fabian M. Suchanek, Lingfei Wu, Yu Chen, Yunyao Li, Bang Liu, Filip Ilievski, Daniel Garijo, Hans Chalupsky, Pedro A. Szekely, Ilias Kanellos, Dimitris Sacharidis, Thanasis Vergoulis, Nurendra Choudhary, Nikhil Rao, Karthik Subbian, Srinivasan H. Sengamedu, Chandan K. Reddy, Friedhelm Victor, Bernhard Haslhofer, George Katsogiannis-Meimarakis, Georgia Koutrika, Shengmin Jin, Danai Koutra, Reza Zafarani, Yulia Tsvetkov, Vidhisha Balachandran, Sachin Kumar, Xiangyu Zhao, Bo Chen, Huifeng Guo, Yejing Wang, Ruiming Tang, Yang Zhang, Wenjie Wang, Peng Wu, Fuli Feng, Xiangnan He:
Accepted Tutorials at The Web Conference 2022. WWW (Companion Volume) 2022: 391-399 - [e9]Tommaso Di Noia, In-Young Ko, Markus Schedl, Carmelo Ardito:
Web Engineering - 22nd International Conference, ICWE 2022, Bari, Italy, July 5-8, 2022, Proceedings. Lecture Notes in Computer Science 13362, Springer 2022, ISBN 978-3-031-09916-8 [contents] - [r3]Markus Schedl, Peter Knees, Brian McFee, Dmitry Bogdanov:
Music Recommendation Systems: Techniques, Use Cases, and Challenges. Recommender Systems Handbook 2022: 927-971 - [r2]Yashar Deldjoo, Markus Schedl, Balázs Hidasi, Yinwei Wei, Xiangnan He:
Multimedia Recommender Systems: Algorithms and Challenges. Recommender Systems Handbook 2022: 973-1014 - [d1]Marta Moscati, Emilia Parada-Cabaleiro, Yashar Deldjoo, Eva Zangerle, Markus Schedl:
Music4All-Onion. Zenodo, 2022 - [i27]Klara Krieg, Emilia Parada-Cabaleiro, Gertraud Medicus, Oleg Lesota, Markus Schedl, Navid Rekabsaz:
Grep-BiasIR: A Dataset for Investigating Gender Representation-Bias in Information Retrieval Results. CoRR abs/2201.07754 (2022) - [i26]Darius Afchar, Alessandro B. Melchiorre, Markus Schedl, Romain Hennequin, Elena V. Epure, Manuel Moussallam:
Explainability in Music Recommender Systems. CoRR abs/2201.10528 (2022) - [i25]Klara Krieg, Emilia Parada-Cabaleiro, Markus Schedl, Navid Rekabsaz:
Do Perceived Gender Biases in Retrieval Results Affect Relevance Judgements? CoRR abs/2203.01731 (2022) - [i24]Christian Ganhör, David Penz, Navid Rekabsaz, Oleg Lesota, Markus Schedl:
Unlearning Protected User Attributes in Recommendations with Adversarial Training. CoRR abs/2206.04500 (2022) - [i23]Peter Müllner, Markus Schedl, Elisabeth Lex, Dominik Kowald:
ReuseKNN: Neighborhood Reuse for Privacy-Aware Recommendations. CoRR abs/2206.11561 (2022) - 2021
- [j37]Yashar Deldjoo, Markus Schedl, Paolo Cremonesi, Gabriella Pasi:
Recommender Systems Leveraging Multimedia Content. ACM Comput. Surv. 53(5): 106:1-106:38 (2021) - [j36]Dominik Kowald, Peter Müllner, Eva Zangerle, Christine Bauer, Markus Schedl, Elisabeth Lex:
Support the underground: characteristics of beyond-mainstream music listeners. EPJ Data Sci. 10(1): 14 (2021) - [j35]Elisabeth Lex, Dominik Kowald, Paul Seitlinger, Thi Ngoc Trang Tran, Alexander Felfernig, Markus Schedl:
Psychology-informed Recommender Systems. Found. Trends Inf. Retr. 15(2): 134-242 (2021) - [j34]Alessandro B. Melchiorre, Navid Rekabsaz, Emilia Parada-Cabaleiro, Stefan Brandl, Oleg Lesota, Markus Schedl:
Investigating gender fairness of recommendation algorithms in the music domain. Inf. Process. Manag. 58(5): 102666 (2021) - [c176]Tomislav Duricic, Dominik Kowald, Markus Schedl, Elisabeth Lex:
My friends also prefer diverse music: homophily and link prediction with user preferences for mainstream, novelty, and diversity in music. ASONAM 2021: 447-454 - [c175]Alessandro B. Melchiorre, Verena Haunschmid, Markus Schedl, Gerhard Widmer:
LEMONS: Listenable Explanations for Music recOmmeNder Systems. ECIR (2) 2021: 531-536 - [c174]Oleg Lesota, Navid Rekabsaz, Daniel Cohen, Klaus Antonius Grasserbauer, Carsten Eickhoff, Markus Schedl:
A Modern Perspective on Query Likelihood with Deep Generative Retrieval Models. ICTIR 2021: 185-195 - [c173]Emilia Parada-Cabaleiro, Maximilian Schmitt, Anton Batliner, Björn W. Schuller, Markus Schedl:
Automatic Recognition of Texture in Renaissance Music. ISMIR 2021: 509-516 - [c172]Harald Victor Schweiger, Emilia Parada-Cabaleiro, Markus Schedl:
Does Track Sequence in User-generated Playlists Matter?. ISMIR 2021: 618-625 - [c171]Alexander Krauck, David Penz, Markus Schedl:
Team JKU-AIWarriors in the ACM Recommender Systems Challenge 2021: Lightweight XGBoost Recommendation Approach Leveraging User Features. RecSys Challenge 2021: 39-43 - [c170]Oleg Lesota, Alessandro B. Melchiorre, Navid Rekabsaz, Stefan Brandl, Dominik Kowald, Elisabeth Lex, Markus Schedl:
Analyzing Item Popularity Bias of Music Recommender Systems: Are Different Genders Equally Affected? RecSys 2021: 601-606 - [c169]Markus Reiter-Haas, Emilia Parada-Cabaleiro, Markus Schedl, Elham Motamedi, Marko Tkalcic, Elisabeth Lex:
Predicting Music Relistening Behavior Using the ACT-R Framework. RecSys 2021: 702-707 - [c168]Navid Rekabsaz, Simone Kopeinik, Markus Schedl:
Societal Biases in Retrieved Contents: Measurement Framework and Adversarial Mitigation of BERT Rankers. SIGIR 2021: 306-316 - [c167]Rosie Jones, Hamed Zamani, Markus Schedl, Ching-Wei Chen, Sravana Reddy, Ann Clifton, Jussi Karlgren, Helia Hashemi, Aasish Pappu, Zahra Nazari, Longqi Yang, Oguz Semerci, Hugues Bouchard, Ben Carterette:
Current Challenges and Future Directions in Podcast Information Access. SIGIR 2021: 1554-1565 - [c166]Navid Rekabsaz, Oleg Lesota, Markus Schedl, Jon Brassey, Carsten Eickhoff:
TripClick: The Log Files of a Large Health Web Search Engine. SIGIR 2021: 2507-2513 - [c165]Christopher Stelzmüller, Sebastian Tanzer, Markus Schedl:
Cross-city Analysis of Location-based Sentiment in User-generated Text. WWW (Companion Volume) 2021: 339-346 - [i22]Dominik Kowald, Peter Müllner, Eva Zangerle, Christine Bauer, Markus Schedl, Elisabeth Lex:
Support the Underground: Characteristics of Beyond-Mainstream Music Listeners. CoRR abs/2102.12188 (2021) - [i21]Navid Rekabsaz, Oleg Lesota, Markus Schedl, Jon Brassey, Carsten Eickhoff:
TripClick: The Log Files of a Large Health Web Search Engine. CoRR abs/2103.07901 (2021) - [i20]Navid Rekabsaz, Simone Kopeinik, Markus Schedl:
Societal Biases in Retrieved Contents: Measurement Framework and Adversarial Mitigation for BERT Rankers. CoRR abs/2104.13640 (2021) - [i19]Rosie Jones, Hamed Zamani, Markus Schedl, Ching-Wei Chen, Sravana Reddy, Ann Clifton, Jussi Karlgren, Helia Hashemi, Aasish Pappu, Zahra Nazari, Longqi Yang, Oguz Semerci, Hugues Bouchard, Ben Carterette:
Current Challenges and Future Directions in Podcast Information Access. CoRR abs/2106.09227 (2021) - [i18]Oleg Lesota, Navid Rekabsaz, Daniel Cohen, Klaus Antonius Grasserbauer, Carsten Eickhoff, Markus Schedl:
A Modern Perspective on Query Likelihood with Deep Generative Retrieval Models. CoRR abs/2106.13618 (2021) - [i17]Yashar Deldjoo, Markus Schedl, Peter Knees:
Content-driven Music Recommendation: Evolution, State of the Art, and Challenges. CoRR abs/2107.11803 (2021) - [i16]Markus Reiter-Haas, Emilia Parada-Cabaleiro, Markus Schedl, Elham Motamedi, Marko Tkalcic, Elisabeth Lex:
Predicting Music Relistening Behavior Using the ACT-R Framework. CoRR abs/2108.02138 (2021) - [i15]Oleg Lesota, Alessandro B. Melchiorre, Navid Rekabsaz, Stefan Brandl, Dominik Kowald, Elisabeth Lex, Markus Schedl:
Analyzing Item Popularity Bias of Music Recommender Systems: Are Different Genders Equally Affected? CoRR abs/2108.06973 (2021) - [i14]Tomislav Duricic, Dominik Kowald, Markus Schedl, Elisabeth Lex:
My friends also prefer diverse music: homophily and link prediction with user preferences for mainstream, novelty, and diversity in music. CoRR abs/2111.00562 (2021) - 2020
- [j33]Markus Schedl, Christine Bauer, Wolfgang Reisinger, Dominik Kowald, Elisabeth Lex:
Listener Modeling and Context-Aware Music Recommendation Based on Country Archetypes. Frontiers Artif. Intell. 3: 508725 (2020) - [j32]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) - [j31]Elisabeth Lex, Dominik Kowald, Markus Schedl:
Modeling Popularity and Temporal Drift of Music Genre Preferences. Trans. Int. Soc. Music. Inf. Retr. 3(1): 17-30 (2020) - [j30]Peter Knees, Markus Schedl, Masataka Goto:
Intelligent User Interfaces for Music Discovery. Trans. Int. Soc. Music. Inf. Retr. 3(1): 165-179 (2020) - [j29]Marko Tkalcic, Markus Schedl, Peter Knees:
Preface to the Special Issue on user modeling for personalized interaction with music. User Model. User Adapt. Interact. 30(2): 195-198 (2020) - [c164]Dominik Kowald, Markus Schedl, Elisabeth Lex:
The Unfairness of Popularity Bias in Music Recommendation: A Reproducibility Study. ECIR (2) 2020: 35-42 - [c163]Meijun Liu, Eva Zangerle, Xiao Hu, Alessandro B. Melchiorre, Markus Schedl:
Pandemics, music, and collective sentiment: evidence from the outbreak of COVID-19. ISMIR 2020: 157-165 - [c162]Kyle Robinson, Dan Brown, Markus Schedl:
User Insights on Diversity in Music Recommendation Lists. ISMIR 2020: 446-453 - [c161]Markus Schedl, Michael Mayr, Peter Knees:
Music Tower Blocks: Multi-Faceted Exploration Interface for Web-Scale Music Access. ICMR 2020: 388-392 - [c160]Alessandro B. Melchiorre, Eva Zangerle, Markus Schedl:
Personality Bias of Music Recommendation Algorithms. RecSys 2020: 533-538 - [c159]Navid Rekabsaz, Markus Schedl:
Do Neural Ranking Models Intensify Gender Bias? SIGIR 2020: 2065-2068 - [c158]Alessandro B. Melchiorre, Markus Schedl:
Personality Correlates of Music Audio Preferences for Modelling Music Listeners. UMAP 2020: 313-317 - [e8]Julie Cumming, Jin Ha Lee, Brian McFee, Markus Schedl, Johanna Devaney, Cory McKay, Eva Zangerle, Timothy de Reuse:
Proceedings of the 21th International Society for Music Information Retrieval Conference, ISMIR 2020, Montreal, Canada, October 11-16, 2020. 2020, ISBN 978-0-9813537-1-5 [contents] - [i13]Dominik Kowald, Elisabeth Lex, Markus Schedl:
Utilizing Human Memory Processes to Model Genre Preferences for Personalized Music Recommendations. CoRR abs/2003.10699 (2020) - [i12]Navid Rekabsaz, Markus Schedl:
Do Neural Ranking Models Intensify Gender Bias? CoRR abs/2005.00372 (2020) - [i11]Markus Schedl, Christine Bauer, Wolfgang Reisinger, Dominik Kowald, Elisabeth Lex:
Listener Modeling and Context-aware Music Recommendation Based on Country Archetypes. CoRR abs/2009.09935 (2020)
2010 – 2019
- 2019
- [j28]Markus Schedl:
Deep Learning in Music Recommendation Systems. Frontiers Appl. Math. Stat. 5: 44 (2019) - [j27]Andreu Vall, Massimo Quadrana, Markus Schedl, Gerhard Widmer:
Order, context and popularity bias in next-song recommendations. Int. J. Multim. Inf. Retr. 8(2): 101-113 (2019) - [j26]Thomas Krismayer, Markus Schedl, Peter Knees, Rick Rabiser:
Predicting user demographics from music listening information. Multim. Tools Appl. 78(3): 2897-2920 (2019) - [j25]Bruce Ferwerda, Emily Yang, Markus Schedl, Marko Tkalcic:
Personality and taxonomy preferences, and the influence of category choice on the user experience for music streaming services. Multim. Tools Appl. 78(14): 20157-20190 (2019) - [j24]Hamed Zamani, Markus Schedl, Paul Lamere, Ching-Wei Chen:
An Analysis of Approaches Taken in the ACM RecSys Challenge 2018 for Automatic Music Playlist Continuation. ACM Trans. Intell. Syst. Technol. 10(5): 57:1-57:21 (2019) - [j23]Yashar Deldjoo, Maurizio Ferrari Dacrema, Mihai Gabriel Constantin, Hamid Eghbal-zadeh, Stefano Cereda, Markus Schedl, Bogdan Ionescu, Paolo Cremonesi:
Movie genome: alleviating new item cold start in movie recommendation. User Model. User Adapt. Interact. 29(2): 291-343 (2019) - [j22]Andreu Vall, Matthias Dorfer, Hamid Eghbal-zadeh, Markus Schedl, Keki Burjorjee, Gerhard Widmer:
Feature-combination hybrid recommender systems for automated music playlist continuation. User Model. User Adapt. Interact. 29(2): 527-572 (2019) - [c157]Yashar Deldjoo, Markus Schedl:
Retrieving Relevant and Diverse Movie Clips Using the MFVCD-7K Multifaceted Video Clip Dataset. CBMI 2019: 1-4 - [c156]Yashar Deldjoo, Markus Schedl, Mehdi Elahi:
Movie Genome Recommender: A Novel Recommender System Based on Multimedia Content. CBMI 2019: 1-4 - [c155]Christine Bauer, Markus Schedl:
Cross-country User Connections in an Online Social Network for Music. CHI Extended Abstracts 2019 - [c154]Christine Bauer, Markus Schedl:
A Cross-Country Investigation of User Connection Patterns in Online Social Networks. HICSS 2019: 1-10 - [c153]Peter Knees, Markus Schedl, Masataka Goto:
Intelligent User Interfaces for Music Discovery: The Past 20 Years and What's to Come. ISMIR 2019: 44-53 - [c152]Peter Knees, Markus Schedl, Rebecca Fiebrink:
Intelligent music interfaces for listening and creation. IUI Companion 2019: 135-136 - [c151]Yashar Deldjoo, Benny Kille, Markus Schedl, Andreas Lommatzsch, Jialie Shen:
The 2019 Multimedia for Recommender System Task: MovieREC and NewsREEL at MediaEval. MediaEval 2019 - [c150]Hossein A. Rahmani, Yashar Deldjoo, Markus Schedl:
A Regression Approach to Movie Rating Prediction Using Multimedia Content and Metadata. MediaEval 2019 - [c149]Christine Bauer, Markus Schedl, Vera Angerer, Stefan Wegenkittl:
Tastalyzer: Audiovisual Exploration of Urban and Rural Variations in Music Taste. ACM Multimedia 2019: 1044-1046 - [c148]Luca Luciano Costanzo, Yashar Deldjoo, Maurizio Ferrari Dacrema, Markus Schedl, Paolo Cremonesi:
Towards Evaluating User Profiling Methods Based on Explicit Ratings on Item Features. IntRS@RecSys 2019: 72-76 - [c147]Markus Schedl:
Genre Differences of Song Lyrics and Artist Wikis: An Analysis of Popularity, Length, Repetitiveness, and Readability. WWW 2019: 3201-3207 - [i10]Dominik Kowald, Elisabeth Lex, Markus Schedl:
Modeling Artist Preferences of Users with Different Music Consumption Patterns for Fair Music Recommendations. CoRR abs/1907.09781 (2019) - [i9]Luca Luciano Costanzo, Yashar Deldjoo, Maurizio Ferrari Dacrema, Markus Schedl, Paolo Cremonesi:
Towards Evaluating User Profiling Methods Based on Explicit Ratings on Item Features. CoRR abs/1908.11055 (2019) - [i8]Dominik Kowald, Markus Schedl, Elisabeth Lex:
The Unfairness of Popularity Bias in Music Recommendation: A Reproducibility Study. CoRR abs/1912.04696 (2019) - [i7]Christine Bauer, Markus Schedl:
Global and country-specific mainstreaminess measures: Definitions, analysis, and usage for improving personalized music recommendation systems. CoRR abs/1912.06933 (2019) - [i6]Markus Schedl, Christine Bauer:
Online Music Listening Culture of Kids and Adolescents: Listening Analysis and Music Recommendation Tailored to the Young. CoRR abs/1912.11564 (2019) - 2018
- [j21]Markus Schedl, Hamed Zamani, Ching-Wei Chen, Yashar Deldjoo, Mehdi Elahi:
Current challenges and visions in music recommender systems research. Int. J. Multim. Inf. Retr. 7(2): 95-116 (2018) - [j20]Markus Schedl, Christine Bauer:
An Analysis of Global and RegionalMainstreaminess for Personalized MusicRecommender Systems. J. Mobile Multimedia 14(1): 95-112 (2018) - [j19]Markus Schedl, Emilia Gómez, Erika S. Trent, Marko Tkalcic, Hamid Eghbal-Zadeh, Agustín Martorell:
On the Interrelation Between Listener Characteristics and the Perception of Emotions in Classical Orchestra Music. IEEE Trans. Affect. Comput. 9(4): 507-525 (2018) - [c146]Christine Bauer, Markus Schedl:
On the Importance of Considering Country-specific Aspects on the Online-Market: An Example of Music Recommendation Considering Country-Specific Mainstream. HICSS 2018: 1-10 - [c145]Mhd Mousa Hamad, Marcin Skowron, Markus Schedl:
Regressing Controversy of Music Artists from Microblogs. ICTAI 2018: 548-555 - [c144]Yashar Deldjoo, Markus Schedl, Paolo Cremonesi, Gabriella Pasi:
Content-Based Multimedia Recommendation Systems: Definition and Application Domains. IIR 2018 - [c143]Christine Bauer, Markus Schedl:
Investigating Cross-Country Relationship between Users' Social Ties and Music Mainstreaminess. ISMIR 2018: 678-686 - [c142]Christian Esswein, Markus Schedl, Eva Zangerle:
geMsearch: Personalized Explorative Music Search. IUI Workshops 2018 - [c141]Yashar Deldjoo, Mihai Gabriel Constantin, Athanasios Dritsas, Bogdan Ionescu, Markus Schedl:
The MediaEval 2018 Movie Recommendation Task: Recommending Movies Using Content. MediaEval 2018 - [c140]Stevan Rudinac, Tat-Seng Chua, Nicolás E. Díaz Ferreyra, Gerald Friedland, Tatjana Gornostaja, Benoit Huet, Rianne Kaptein, Krister Lindén, Marie-Francine Moens, Jaakko Peltonen, Miriam Redi, Markus Schedl, David A. Shamma, Alan F. Smeaton, Lexing Xie:
Rethinking Summarization and Storytelling for Modern Social Multimedia. MMM (1) 2018: 632-644 - [c139]Yashar Deldjoo, Mihai Gabriel Constantin, Bogdan Ionescu, Markus Schedl, Paolo Cremonesi:
MMTF-14K: a multifaceted movie trailer feature dataset for recommendation and retrieval. MMSys 2018: 450-455 - [c138]Yashar Deldjoo, Mihai Gabriel Constantin, Hamid Eghbal-Zadeh, Bogdan Ionescu, Markus Schedl, Paolo Cremonesi:
Audio-visual encoding of multimedia content for enhancing movie recommendations. RecSys 2018: 455-459 - [c137]Ching-Wei Chen, Paul Lamere, Markus Schedl, Hamed Zamani:
Recsys challenge 2018: automatic music playlist continuation. RecSys 2018: 527-528 - [c136]Yashar Deldjoo, Markus Schedl, Balázs Hidasi, Peter Knees:
Multimedia recommender systems. RecSys 2018: 537-538 - [c135]Andreu Vall, Matthias Dorfer, Markus Schedl, Gerhard Widmer:
A hybrid approach to music playlist continuation based on playlist-song membership. SAC 2018: 1374-1382 - [c134]Eva Zangerle, Martin Pichl, Markus Schedl:
Culture-Aware Music Recommendation. UMAP 2018: 357-358 - [c133]Markus Schedl, Eelco Wiechert, Christine Bauer:
The Effects of Real-world Events on Music Listening Behavior: An Intervention Time Series Analysis. WWW (Companion Volume) 2018: 75-76 - [i5]Andreu Vall, Matthias Dorfer, Markus Schedl, Gerhard Widmer:
A Hybrid Approach to Music Playlist Continuation Based on Playlist-Song Membership. CoRR abs/1805.09557 (2018) - [i4]Andreu Vall, Massimo Quadrana, Markus Schedl, Gerhard Widmer:
The Importance of Song Context and Song Order in Automated Music Playlist Generation. CoRR abs/1807.04690 (2018) - [i3]Hamed Zamani, Markus Schedl, Paul Lamere, Ching-Wei Chen:
An Analysis of Approaches Taken in the ACM RecSys Challenge 2018 for Automatic Music Playlist Continuation. CoRR abs/1810.01520 (2018) - 2017
- [j18]Markus Schedl:
Investigating country-specific music preferences and music recommendation algorithms with the LFM-1b dataset. Int. J. Multim. Inf. Retr. 6(1): 71-84 (2017) - [j17]Markus Schedl, Yi-Hsuan Yang, Perfecto Herrera-Boyer:
Introduction to Intelligent Music Systems and Applications. ACM Trans. Intell. Syst. Technol. 8(2): 17:1-17:8 (2017) - [c132]Thomas Krismayer, Markus Schedl, Peter Knees, Rick Rabiser:
Prediction of User Demographics from Music Listening Habits. CBMI 2017: 8:1-8:7 - [c131]Yashar Deldjoo, Paolo Cremonesi, Markus Schedl, Massimo Quadrana:
The effect of different video summarization models on the quality of video recommendation based on low-level visual features. CBMI 2017: 20:1-20:6 - [c130]Haukur Pálmason, Björn Þór Jónsson, Markus Schedl, Peter Knees:
Music Genre Classification Revisited: An In-Depth Examination Guided by Music Experts. CMMR 2017: 49-62 - [c129]Marcin Skowron, Florian Lemmerich, Bruce Ferwerda, Markus Schedl:
Predicting Genre Preferences from Cultural and Socio-Economic Factors for Music Retrieval. ECIR 2017: 561-567 - [c128]Martin Pichl, Eva Zangerle, Günther Specht, Markus Schedl:
Mining Culture-Specific Music Listening Behavior from Social Media Data. ISM 2017: 208-215 - [c127]Markus Schedl, Florian Lemmerich, Bruce Ferwerda, Marcin Skowron, Peter Knees:
Indicators of Country Similarity in Terms of Music Taste, Cultural, and Socio-economic Factors. ISM 2017: 308-311 - [c126]Markus Schedl, Bruce Ferwerda:
Large-Scale Analysis of Group-Specific Music Genre Taste from Collaborative Tags. ISM 2017: 479-482 - [c125]Meijun Liu, Xiao Hu, Markus Schedl:
Artist Preferences and Cultural, Socio-Economic Distances Across Countries: A Big Data Perspective. ISMIR 2017: 103-111 - [c124]Markus Schedl:
Intelligent User Interfaces for Social Music Discovery and Exploration of Large-scale Music Repositories. HUMANIZE@IUI 2017: 7-11 - [c123]Mark P. Graus, Bruce Ferwerda, Markus Schedl, Marko Tkalcic, Martijn C. Willemsen, Panagiotis Germanakos:
IUI'17 Companion-Workshop Summary for HUMANIZE'17. IUI Companion 2017: 13-15 - [c122]Khaled Koutini, Alina Imenina, Matthias Dorfer, Alexander Gruber, Markus Schedl:
MediaEval 2017 AcousticBrainz Genre Task: Multilayer Perceptron Approach. MediaEval 2017 - [c121]Markus Schedl, Christine Bauer:
Introducing Global and Regional Mainstreaminess for Improving Personalized Music Recommendation. MoMM 2017: 74-81 - [c120]Bruce Ferwerda, Marko Tkalcic, Markus Schedl:
Personality Traits and Music Genre Preferences: How Music Taste Varies Over Age Groups. RecTemp@RecSys 2017: 16-20 - [c119]Andreu Vall, Hamid Eghbal-zadeh, Matthias Dorfer, Markus Schedl, Gerhard Widmer:
Music Playlist Continuation by Learning from Hand-Curated Examples and Song Features: Alleviating the Cold-Start Problem for Rare and Out-of-Set Songs. DLRS@RecSys 2017: 46-54 - [c118]Markus Schedl, Peter Knees, Fabien Gouyon:
New Paths in Music Recommender Systems Research. RecSys 2017: 392-393 - [c117]Andreu Vall, Massimo Quadrana, Markus Schedl, Gerhard Widmer, Paolo Cremonesi:
The Importance of Song Context in Music Playlists. RecSys Posters 2017 - [c116]Bruce Ferwerda, Mark P. Graus, Andreu Vall, Marko Tkalcic, Markus Schedl:
How item discovery enabled by diversity leads to increased recommendation list attractiveness. SAC 2017: 1693-1696 - [c115]Haukur Pálmason, Björn Þór Jónsson, Laurent Amsaleg, Markus Schedl, Peter Knees:
On Competitiveness of Nearest-Neighbor-Based Music Classification: A Methodological Critique. SISAP 2017: 275-283 - [c114]Bruce Ferwerda, Marko Tkalcic, Markus Schedl:
Personality Traits and Music Genres: What Do People Prefer to Listen To? UMAP 2017: 285-288 - [c113]Christine Bauer, Markus Schedl:
Introducing Surprise and Opposition by Design in Recommender Systems. UMAP (Adjunct Publication) 2017: 350-353 - [c112]Markus Schedl, Christine Bauer:
Distance- and Rank-based Music Mainstreaminess Measurement. UMAP (Adjunct Publication) 2017: 364-367 - [e7]Mark P. Graus, Bruce Ferwerda, Markus Schedl, Marko Tkalcic, Martijn C. Willemsen, Panagiotis Germanakos:
Proceedings of the 2017 ACM Workshop on Theory-Informed User Modeling for Tailoring and Personalizing Interfaces, HUMANIZE@IUI 2017, Limassol, Cyprus, March 13, 2017. ACM 2017, ISBN 978-1-4503-4905-5 [contents] - [i2]Andreu Vall, Hamid Eghbal-zadeh, Matthias Dorfer, Markus Schedl:
Music Playlist Continuation by Learning from Hand-Curated Examples and Song Features. CoRR abs/1705.08283 (2017) - [i1]Markus Schedl, Hamed Zamani, Ching-Wei Chen, Yashar Deldjoo, Mehdi Elahi:
Current Challenges and Visions in Music Recommender Systems Research. CoRR abs/1710.03208 (2017) - 2016
- [b1]Peter Knees, Markus Schedl:
Music Similarity and Retrieval - An Introduction to Audio- and Web-based Strategies. The Information Retrieval Series 36, Springer 2016, ISBN 978-3-662-49720-3, pp. 1-254 - [c111]David Hauger, Markus Schedl:
Music Tweet Map: A browsing interface to explore the microblogosphere of music. CBMI 2016: 1-4 - [c110]Markus Schedl, David Hauger, Marko Tkalcic, Mark S. Melenhorst, Cynthia C. S. Liem:
A dataset of multimedia material about classical music: PHENICX-SMM. CBMI 2016: 1-4 - [c109]Markus Schedl, Fang Zhou:
Fusing Web and Audio Predictors to Localize the Origin of Music Pieces for Geospatial Retrieval. ECIR 2016: 322-334 - [c108]Markus Schedl, Hamid Eghbal-Zadeh, Emilia Gómez, Marko Tkalcic:
An Analysis of Agreement in Classical Music Perception and its Relationship to Listener Characteristics. ISMIR 2016: 578-583 - [c107]Markus Schedl:
The LFM-1b Dataset for Music Retrieval and Recommendation. ICMR 2016: 103-110 - [c106]Marko Tkalcic, Markus Schedl, Cynthia C. S. Liem, Mark S. Melenhorst:
Personalized Retrieval and Browsing of Classical Music and Supporting Multimedia Material. ICMR 2016: 393-396 - [c105]Bruce Ferwerda, Markus Schedl, Marko Tkalcic:
Using Instagram Picture Features to Predict Users' Personality. MMM (1) 2016: 850-861 - [c104]Markus Schedl, Mark S. Melenhorst, Cynthia C. S. Liem, Agustín Martorell, Oscar Mayor, Marko Tkalcic:
A personality-based adaptive system for visualizing classical music performances. MMSys 2016: 15:1-15:7 - [c103]Bruce Ferwerda, Markus Schedl:
Personality-Based User Modeling for Music Recommender Systems. ECML/PKDD (3) 2016: 254-257 - [c102]Bruce Ferwerda, Mark P. Graus, Andreu Vall, Marko Tkalcic, Markus Schedl:
The Influence of Users' Personality Traits on Satisfaction and Attractiveness of Diversified Recommendation Lists. EMPIRE@RecSys 2016: 43-47 - [c101]Bruce Ferwerda, Markus Schedl:
Investigating the Relationship Between Diversity in Music Consumption Behavior and Cultural Dimensions: A Cross-Country Analysis. UMAP (Extended Proceedings) 2016 - [c100]Bruce Ferwerda, Andreu Vall, Marko Tkalcic, Markus Schedl:
Exploring Music Diversity Needs Across Countries. UMAP 2016: 287-288 - [c99]Marcin Skowron, Marko Tkalcic, Bruce Ferwerda, Markus Schedl:
Fusing Social Media Cues: Personality Prediction from Twitter and Instagram. WWW (Companion Volume) 2016: 107-108 - [c98]Bruce Ferwerda, Markus Schedl, Marko Tkalcic:
Personality Traits and the Relationship with (Non-) Disclosure Behavior on Facebook. WWW (Companion Volume) 2016: 565-568 - 2015
- [c97]Markus Schedl, Mats Sjöberg, Ionut Mironica, Bogdan Ionescu, Vu Lam Quang, Yu-Gang Jiang, Claire-Hélène Demarty:
VSD2014: A dataset for violent scenes detection in hollywood movies and web videos. CBMI 2015: 1-6 - [c96]Bruce Ferwerda, Emily Yang, Markus Schedl, Marko Tkalcic:
Personality Traits Predict Music Taxonomy Preferences. CHI Extended Abstracts 2015: 2241-2246 - [c95]Markus Schedl, David Hauger, Katayoun Farrahi, Marko Tkalcic:
On the Influence of User Characteristics on Music Recommendation Algorithms. ECIR 2015: 339-345 - [c94]Hamid Eghbal-zadeh, Markus Schedl, Gerhard Widmer:
Timbral modeling for music artist recognition using i-vectors. EUSIPCO 2015: 1286-1290 - [c93]Markus Schedl:
Towards Personalizing Classical Music Recommendations. ICDM Workshops 2015: 1366-1367 - [c92]Cynthia C. S. Liem, Emilia Gómez, Markus Schedl:
PHENICX: Innovating the classical music experience. ICME Workshops 2015: 1-4 - [c91]Andreu Vall, Marcin Skowron, Peter Knees, Markus Schedl:
Improving Music Recommendations with a Weighted Factorization of the Tagging Activity. ISMIR 2015: 65-71 - [c90]Hamid Eghbal-zadeh, Bernhard Lehner, Markus Schedl, Gerhard Widmer:
I-Vectors for Timbre-Based Music Similarity and Music Artist Classification. ISMIR 2015: 554-560 - [c89]Michael Mayr, Thomas Hintersteiner, Michael Weingartner, Florian Schröckeneder, Peter Knees, Markus Schedl:
JKU-Satellite at MediaEval 2015: An Intuitive Approach to Locate Single Pictures Within a Session. MediaEval 2015 - [c88]Ionut Mironica, Bogdan Ionescu, Mats Sjöberg, Markus Schedl, Marcin Skowron:
RFA at MediaEval 2015 Affective Impact of Movies Task: A Multimodal Approach. MediaEval 2015 - [c87]Mats Sjöberg, Yoann Baveye, Hanli Wang, Vu Lam Quang, Bogdan Ionescu, Emmanuel Dellandréa, Markus Schedl, Claire-Hélène Demarty, Liming Chen:
The MediaEval 2015 Affective Impact of Movies Task. MediaEval 2015 - [c86]Michael Gillhofer, Markus Schedl:
Iron Maiden While Jogging, Debussy for Dinner? - An Analysis of Music Listening Behavior in Context. MMM (2) 2015: 380-391 - [c85]Markus Schedl:
Listener-aware Music Search and Recommendation. MUSE@PKDD/ECML 2015: 18 - [c84]Markus Schedl:
Listener-Aware Music Recommendation from Sensor and Social Media Data. ECML/PKDD (3) 2015: 213-217 - [c83]Bruce Ferwerda, Markus Schedl, Marko Tkalcic:
Predicting Personality Traits with Instagram Pictures. EMPIRE@RecSys 2015: 7-10 - [c82]Markus Schedl, David Hauger:
Tailoring Music Recommendations to Users by Considering Diversity, Mainstreaminess, and Novelty. SIGIR 2015: 947-950 - [c81]Peter Knees, Markus Schedl:
Music Retrieval and Recommendation: A Tutorial Overview. SIGIR 2015: 1133-1136 - [c80]Bruce Ferwerda, Markus Schedl, Marko Tkalcic:
Personality & Emotional States: Understanding Users' Music Listening Needs. UMAP Workshops 2015 - [c79]Marko Tkalcic, Bruce Ferwerda, David Hauger, Markus Schedl:
Personality Correlates for Digital Concert Program Notes. UMAP 2015: 364-369 - [r1]Markus Schedl, Peter Knees, Brian McFee, Dmitry Bogdanov, Marius Kaminskas:
Music Recommender Systems. Recommender Systems Handbook 2015: 453-492 - 2014
- [j16]Markus Schedl, Emilia Gómez, Julián Urbano:
Music Information Retrieval: Recent Developments and Applications. Found. Trends Inf. Retr. 8(2-3): 127-261 (2014) - [j15]Markus Schedl, David Hauger, Julián Urbano:
Harvesting microblogs for contextual music similarity estimation: a co-occurrence-based framework. Multim. Syst. 20(6): 693-705 (2014) - [c78]Claire-Hélène Demarty, Bogdan Ionescu, Yu-Gang Jiang, Vu Lam Quang, Markus Schedl, Cédric Penet:
Benchmarking Violent Scenes Detection in movies. CBMI 2014: 1-6 - [c77]Katayoun Farrahi, Markus Schedl, Andreu Vall, David Hauger, Marko Tkalcic:
Impact of Listening Behavior on Music Recommendation. ISMIR 2014: 483-488 - [c76]Mats Sjöberg, Bogdan Ionescu, Yu-Gang Jiang, Vu Lam Quang, Markus Schedl, Claire-Hélène Demarty:
The MediaEval 2014 Affect Task: Violent Scenes Detection. MediaEval 2014 - [c75]Mats Sjöberg, Ionut Mironica, Markus Schedl, Bogdan Ionescu:
FAR at MediaEval 2014 Violent Scenes Detection: A Concept-based Fusion Approach. MediaEval 2014 - [c74]Markus Schedl, Georg Breitschopf, Bogdan Ionescu:
Mobile Music Genius: Reggae at the Beach, Metal on a Friday Night? ICMR 2014: 507 - [c73]Markus Schedl, Marko Tkalcic:
Genre-based Analysis of Social Media Data on Music Listening Behavior: Are Fans of Classical Music Really Averse to Social Media? WISMM 2014: 9-13 - [c72]Markus Schedl, Dominik Schnitzer:
Location-Aware Music Artist Recommendation. MMM (2) 2014: 205-213 - [c71]Markus Schedl:
Social media and classical music?: a first analysis within the PHENICX project: "performances as highly enriched aNd interactive concert eXperiences". SoMeRA@SIGIR 2014: 43-44 - [c70]Markus Schedl, Andreu Vall, Katayoun Farrahi:
User geospatial context for music recommendation in microblogs. SIGIR 2014: 987-990 - [c69]Markus Schedl, Peter Knees, Jialie Shen:
SoMeRA 2014: social media retrieval and analysis workshop. SIGIR 2014: 1297 - [c68]Bruce Ferwerda, Markus Schedl:
Enhancing Music Recommender Systems with Personality Information and Emotional States: A Proposal. UMAP Workshops 2014 - [c67]Marko Tkalcic, Bruce Ferwerda, Markus Schedl, Cynthia C. S. Liem, Mark S. Melenhorst, Ante Odic, Andrej Kosir:
Using Social Media Mining for Estimating Theory of Planned Behaviour Parameters. UMAP Workshops 2014 - [p3]Markus Schedl, Mohamed Sordo, Noam Koenigstein, Udi Weinsberg:
Mining User Generated Data for Music Information Retrieval. Mining User Generated Content 2014: 67-96 - [e6]Martha A. Larson, Bogdan Ionescu, Xavier Anguera, Maria Eskevich, Pavel Korshunov, Markus Schedl, Mohammad Soleymani, Georgios Petkos, Richard F. E. Sutcliffe, Jaeyoung Choi, Gareth J. F. Jones:
Working Notes Proceedings of the MediaEval 2014 Workshop, Barcelona, Catalunya, Spain, October 16-17, 2014. CEUR Workshop Proceedings 1263, CEUR-WS.org 2014 [contents] - [e5]Markus Schedl, Peter Knees, Jialie Shen:
SoMeRA'14, Proceedings of the First ACM International Workshop on Social Media Retrieval and Analysis, July 11, 2014, Gold Coast, Queensland, Australia. ACM 2014, ISBN 978-1-4503-3022-0 [contents] - 2013
- [j14]Peter Knees, Markus Schedl, Òscar Celma:
Hybrid music information retrieval. Int. J. Multim. Inf. Retr. 2(1): 1-2 (2013) - [j13]Julián Urbano, Markus Schedl:
Minimal test collections for low-cost evaluation of Audio Music Similarity and Retrieval systems. Int. J. Multim. Inf. Retr. 2(1): 59-70 (2013) - [j12]Julián Urbano, Markus Schedl, Xavier Serra:
Evaluation in Music Information Retrieval. J. Intell. Inf. Syst. 41(3): 345-369 (2013) - [j11]Markus Schedl, Arthur Flexer, Julián Urbano:
The neglected user in music information retrieval research. J. Intell. Inf. Syst. 41(3): 523-539 (2013) - [j10]Peter Knees, Markus Schedl:
A survey of music similarity and recommendation from music context data. ACM Trans. Multim. Comput. Commun. Appl. 10(1): 2:1-2:21 (2013) - [c66]Markus Schedl:
Leveraging Microblogs for Spatiotemporal Music Information Retrieval. ECIR 2013: 796-799 - [c65]David Hauger, Markus Schedl, Andrej Kosir, Marko Tkalcic:
The Million Musical Tweet Dataset - What We Can Learn From Microblogs. ISMIR 2013: 189-194 - [c64]Claire-Hélène Demarty, Cédric Penet, Markus Schedl, Bogdan Ionescu, Vu Lam Quang, Yu-Gang Jiang:
The MediaEval 2013 Affect Task: Violent Scenes Detection. MediaEval 2013 - [c63]Cynthia C. S. Liem, Nicola Orio, Geoffroy Peeters, Markus Schedl:
MusiClef 2013: Soundtrack Selection for Commercials. MediaEval 2013 - [c62]Mats Sjöberg, Jan Schlüter, Bogdan Ionescu, Markus Schedl:
FAR at MediaEval 2013 Violent Scenes Detection: Concept-based Violent Scenes Detection in Movies. MediaEval 2013 - [c61]Bogdan Ionescu, Jan Schlüter, Ionut Mironica, Markus Schedl:
A naive mid-level concept-based fusion approach to violence detection in Hollywood movies. ICMR 2013: 215-222 - [c60]Markus Schedl, Emilia Gómez, Masataka Goto:
Multimedia information retrieval: music and audio. ACM Multimedia 2013: 1117-1118 - [c59]Markus Schedl, Nicola Orio, Cynthia C. S. Liem, Geoffroy Peeters:
A professionally annotated and enriched multimodal data set on popular music. MMSys 2013: 78-83 - [c58]Markus Schedl:
Ameliorating Music Recommendation: Integrating Music Content, Music Context, and User Context for Improved Music Retrieval and Recommendation. MoMM 2013: 3 - [c57]Claus Schabetsberger, Markus Schedl:
Personalized Music Recommendation in a Mobile Environment. MoMM 2013: 63 - [c56]Marius Kaminskas, Francesco Ricci, Markus Schedl:
Location-aware music recommendation using auto-tagging and hybrid matching. RecSys 2013: 17-24 - [c55]Markus Schedl, Dominik Schnitzer:
Hybrid retrieval approaches to geospatial music recommendation. SIGIR 2013: 793-796 - [c54]Peter Knees, Markus Schedl:
Music similarity and retrieval. SIGIR 2013: 1125 - [p2]Markus Schedl:
Exploiting Social Media for Music Information Retrieval. Social Media Retrieval 2013: 449-478 - [e4]Martha A. Larson, Xavier Anguera, Timo Reuter, Gareth J. F. Jones, Bogdan Ionescu, Markus Schedl, Tomas Piatrik, Claudia Hauff, Mohammad Soleymani:
Proceedings of the MediaEval 2013 Multimedia Benchmark Workshop, Barcelona, Spain, October 18-19, 2013. CEUR Workshop Proceedings 1043, CEUR-WS.org 2013 [contents] - 2012
- [j9]Markus Schedl:
#nowplaying Madonna: a large-scale evaluation on estimating similarities between music artists and between movies from microblogs. Inf. Retr. 15(3-4): 183-217 (2012) - [j8]Dominik Schnitzer, Arthur Flexer, Markus Schedl, Gerhard Widmer:
Local and global scaling reduce hubs in space. J. Mach. Learn. Res. 13: 2871-2902 (2012) - [c53]David Hauger, Markus Schedl:
Exploring Geospatial Music Listening Patterns in Microblog Data. Adaptive Multimedia Retrieval 2012: 133-146 - [c52]Klaus Seyerlehner, Markus Schedl, Reinhard Sonnleitner, David Hauger, Bogdan Ionescu:
From Improved Auto-Taggers to Improved Music Similarity Measures. Adaptive Multimedia Retrieval 2012: 193-202 - [c51]Markus Schedl, David Hauger, Dominik Schnitzer:
A model for serendipitous music retrieval. CaRR 2012: 10-13 - [c50]Nicola Orio, Cynthia C. S. Liem, Geoffroy Peeters, Markus Schedl:
MusiClef: Multimodal Music Tagging Task. CLEF 2012: 36-41 - [c49]Sebastian Böck, Markus Schedl:
Polyphonic piano note transcription with recurrent neural networks. ICASSP 2012: 121-124 - [c48]Sebastian Böck, Florian Krebs, Markus Schedl:
Evaluating the Online Capabilities of Onset Detection Methods. ISMIR 2012: 49-54 - [c47]Julián Urbano, J. Stephen Downie, Brian McFee, Markus Schedl:
How Significant is Statistically Significant? The case of Audio Music Similarity and Retrieval. ISMIR 2012: 181-186 - [c46]Markus Schedl, Arthur Flexer:
Putting the User in the Center of Music Information Retrieval. ISMIR 2012: 385-390 - [c45]Bogdan Ionescu, Ionut Mironica, Klaus Seyerlehner, Peter Knees, Jan Schlüter, Markus Schedl, Horia Cucu, Andi Buzo, Patrick Lambert:
ARF @ MediaEval 2012: Multimodal Video Classification. MediaEval 2012 - [c44]Cynthia C. S. Liem, Nicola Orio, Geoffroy Peeters, Markus Schedl:
Brave New Task: MusiClef Multimodal Music Tagging. MediaEval 2012 - [c43]Jan Schlüter, Bogdan Ionescu, Ionut Mironica, Markus Schedl:
ARF @ MediaEval 2012: An Uninformed Approach to Violence Detection in Hollywood Movies. MediaEval 2012 - [c42]Sebastian Huber, Markus Schedl, Peter Knees:
nepDroid: an intelligent mobile music player. ICMR 2012: 57 - [c41]Markus Schedl, David Hauger:
Mining microblogs to infer music artist similarity and cultural listening patterns. WWW (Companion Volume) 2012: 877-886 - [c40]Julián Urbano, Markus Schedl:
Towards minimal test collections for evaluation of audio music similarity and retrieval. WWW (Companion Volume) 2012: 917-924 - [p1]Markus Schedl, Sebastian Stober, Emilia Gómez, Nicola Orio, Cynthia C. S. Liem:
User-Aware Music Retrieval. Multimodal Music Processing 2012: 135-156 - [e3]Meinard Müller, Masataka Goto, Markus Schedl:
Multimodal Music Processing. Dagstuhl Follow-Ups 3, Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik, Germany 2012, ISBN 978-3-939897-37-8 [contents] - 2011
- [j7]Markus Schedl, Gerhard Widmer, Peter Knees, Tim Pohle:
A music information system automatically generated via Web content mining techniques. Inf. Process. Manag. 47(3): 426-439 (2011) - [j6]Markus Schedl, Tim Pohle, Peter Knees, Gerhard Widmer:
Exploring the music similarity space on the web. ACM Trans. Inf. Syst. 29(3): 14:1-14:24 (2011) - [c39]Markus Schedl, Peter Knees:
Personalization in Multimodal Music Retrieval. Adaptive Multimedia Retrieval 2011: 58-71 - [c38]Iván Cantador, José Carlos Cortizo, Francisco M. Carrero, José A. Troyano, Paolo Rosso, Markus Schedl:
Overview of the third international workshop on search and mining user-generated contents. CIKM 2011: 2625-2626 - [c37]Dominik Schnitzer, Arthur Flexer, Markus Schedl, Gerhard Widmer:
Using Mutual Proximity to Improve Content-Based Audio Similarity. ISMIR 2011: 79-84 - [c36]Markus Schedl, Peter Knees, Sebastian Böck:
Investigating the Similarity Space of Music Artists on the Micro-Blogosphere. ISMIR 2011: 323-328 - [c35]Nicola Orio, David Rizo, Riccardo Miotto, Markus Schedl, Nicola Montecchio, Olivier Lartillot:
MusiCLEF: a Benchmark Activity in Multimodal Music Information Retrieval. ISMIR 2011: 603-608 - [c34]Markus Schedl, Christian Höglinger, Peter Knees:
Large-scale music exploration in hierarchically organized landscapes using prototypicality information. ICMR 2011: 8 - [e2]Marcin Detyniecki, Peter Knees, Andreas Nürnberger, Markus Schedl, Sebastian Stober:
Adaptive Multimedia Retrieval. Context, Exploration, and Fusion - 8th International Workshop, AMR 2010, Linz, Austria, August 17-18, 2010, Revised Selected Papers. Lecture Notes in Computer Science 6817, Springer 2011, ISBN 978-3-642-27168-7 [contents] - [e1]Iván Cantador, Francisco M. Carrero, José Carlos Cortizo, Paolo Rosso, Markus Schedl, José A. Troyano:
Proceedings of the 3rd International CIKM Workshop on Search and Mining User-Generated Contents, SMUC 2011, Glasgow, United Kingdom, October 28, 2011. ACM 2011, ISBN 978-1-4503-0949-3 [contents] - 2010
- [j5]Markus Schedl, Tim Pohle:
Enlightening the sun - A user interface to explore music artists via multimedia content. Multim. Tools Appl. 49(1): 101-118 (2010) - [c33]Markus Schedl, Cornelia Schiketanz, Klaus Seyerlehner:
Country of origin determination via Web mining techniques. ICME 2010: 1451-1456 - [c32]Markus Schedl, Tim Pohle, Noam Koenigstein, Peter Knees:
What's Hot? Estimating Country-specific Artist Popularity. ISMIR 2010: 117-122 - [c31]Markus Schedl:
On the Use of Microblogging Posts for Similarity Estimation and Artist Labeling. ISMIR 2010: 447-452 - [c30]Peter Knees, Markus Schedl, Tim Pohle, Klaus Seyerlehner, Gerhard Widmer:
Supervised and Unsupervised Web Document Filtering Techniques to Improve Text-Based Music Retrieval. ISMIR 2010: 543-548 - [c29]Markus Schedl, Klaus Seyerlehner, Dominik Schnitzer, Gerhard Widmer, Cornelia Schiketanz:
Three web-based heuristics to determine a person's or institution's country of origin. SIGIR 2010: 801-802
2000 – 2009
- 2009
- [c28]Maarten Grachten, Markus Schedl, Tim Pohle, Gerhard Widmer:
The ISMIR Cloud: A Decade of ISMIR Conferences at Your Fingertips. ISMIR 2009: 63-68 - [c27]Tim Pohle, Dominik Schnitzer, Markus Schedl, Peter Knees, Gerhard Widmer:
On Rhythm and General Music Similarity. ISMIR 2009: 525-530 - [c26]Peter Knees, Tim Pohle, Markus Schedl, Dominik Schnitzer, Klaus Seyerlehner, Gerhard Widmer:
Augmenting Text-based Music Retrieval with Audio Similarity: Advantages and Limitations. ISMIR 2009: 579-584 - 2008
- [c25]Markus Schedl, Peter Knees, Tim Pohle, Gerhard Widmer:
Towards an Automatically Generated Music Information System Via Web Content Mining. ECIR 2008: 585-590 - [c24]Peter Knees, Tim Pohle, Markus Schedl, Dominik Schnitzer, Klaus Seyerlehner:
A Document-Centered Approach to a Natural Language Music Search Engine. ECIR 2008: 627-631 - [c23]Markus Dopler, Markus Schedl, Tim Pohle, Peter Knees:
Accessing Music Collections Via Representative Cluster Prototypes in a Hierarchical Organization Scheme. ISMIR 2008: 179-184 - [c22]Markus Schedl, Tim Pohle:
Exploring Music Artists via Descriptive Terms and Multimedia Content. SAMT 2008: 137-148 - 2007
- [j4]Peter Knees, Markus Schedl, Tim Pohle, Gerhard Widmer:
Exploring Music Collections in Virtual Landscapes. IEEE Multim. 14(3): 46-54 (2007) - [j3]Tim Pohle, Peter Knees, Markus Schedl, Elias Pampalk, Gerhard Widmer:
"Reinventing the Wheel": A Novel Approach to Music Player Interfaces. IEEE Trans. Multim. 9(3): 567-575 (2007) - [c21]Markus Schedl, Gerhard Widmer:
Automatically Detecting Members and Instrumentation of Music Bands Via Web Content Mining. Adaptive Multimedia Retrieval 2007: 122-133 - [c20]Tim Pohle, Peter Knees, Markus Schedl, Gerhard Widmer:
Building an Interactive Next-Generation Artist Recommender Based on Automatically Derived High-Level Concepts. CBMI 2007: 336-343 - [c19]Tim Pohle, Peter Knees, Markus Schedl, Gerhard Widmer:
Meaningfully Browsing Music Services. ISMIR 2007: 115-116 - [c18]Markus Schedl, Gerhard Widmer, Tim Pohle, Klaus Seyerlehner:
Web-Based Detection of Music Band Members and Line-Up. ISMIR 2007: 117-118 - [c17]Gijs Geleijnse, Markus Schedl, Peter Knees:
The Quest for Ground Truth in Musical Artist Tagging in the Social Web Era. ISMIR 2007: 525-530 - [c16]Peter Knees, Tim Pohle, Markus Schedl, Gerhard Widmer:
A music search engine built upon audio-based and web-based similarity measures. SIGIR 2007: 447-454 - [c15]Markus Schedl, Peter Knees, Klaus Seyerlehner, Tim Pohle:
The CoMIRVA Toolkit for Visualizing Music-Related Data. EuroVis 2007: 147-154 - 2006
- [c14]Markus Schedl, Peter Knees, Tim Pohle, Gerhard Widmer:
Towards Automatic Retrieval of Album Covers. ECIR 2006: 531-534 - [c13]Markus Schedl, Peter Knees, Gerhard Widmer:
Investigating Web-Based Approaches to Revealing Prototypical Music Artists in Genre Taxonomies. ICDIM 2006: 519-524 - [c12]Tim Pohle, Peter Knees, Markus Schedl, Gerhard Widmer:
Independent Component Analysis for Music Similarity Computation. ISMIR 2006: 228-233 - [c11]Markus Schedl, Tim Pohle, Peter Knees, Gerhard Widmer:
Assigning and Visualizing Music Genres by Web-based Co-Occurrence Analysis. ISMIR 2006: 260-265 - [c10]Peter Knees, Tim Pohle, Markus Schedl, Gerhard Widmer:
Combining audio-based similarity with web-based data to accelerate automatic music playlist generation. Multimedia Information Retrieval 2006: 147-154 - [c9]Peter Knees, Markus Schedl, Tim Pohle, Gerhard Widmer:
An innovative three-dimensional user interface for exploring music collections enriched. ACM Multimedia 2006: 17-24 - 2005
- [c8]Markus Schedl, Peter Knees, Gerhard Widmer:
Improving Prototypical Artist Detection by Penalizing Exorbitant Popularity. CMMR 2005: 196-200 - [c7]Gerhard Widmer, Simon Dixon, Arthur Flexer, Werner Goebl, Peter Knees, Søren Tjagvad Madsen, Elias Pampalk, Tim Pohle, Markus Schedl, Asmir Tobudic:
The Machine Learning and Intelligent Music Processing Group at the Austrian Research Institute for Artificial Intelligence (öFAI), Vienna. ICMC 2005 - [c6]Markus Schedl, Peter Knees, Gerhard Widmer:
Discovering and Visualizing Prototypical Artists by Web-Based Co-Occurrence Analysis. ISMIR 2005: 21-28 - [c5]Peter Knees, Markus Schedl, Gerhard Widmer:
Multiple Lyrics Alignment: Automatic Retrieval of Song Lyrics. ISMIR 2005: 564-569 - [c4]Markus Schedl, Peter Knees, Gerhard Widmer:
Interactive Poster: Using CoMIRVA for Visualizing Similarities Between Music Artists. IEEE Visualization 2005: 89 - 2004
- [j2]Gerd Hirzinger, Norbert Sporer, Markus Schedl, Jörg Butterfaß, Markus Grebenstein:
Torque-Controlled Lightweight Arms and Articulated Hands: Do We Reach Technological Limits Now? Int. J. Robotics Res. 23(4-5): 331-340 (2004) - 2003
- [j1]Gerd Hirzinger, Bernhard Brunner, Klaus Landzettel, Norbert Sporer, Jörg Butterfaß, Markus Schedl:
Space Robotics-DLR's Telerobotic Concepts, Lightweight Arms and Articulated Hands. Auton. Robots 14(2-3): 127-145 (2003) - 2002
- [c3]Gerd Hirzinger, Norbert Sporer, Alin Albu-Schäffer, Matthias Hähnle, R. Krenn, A. Pascucci, Markus Schedl:
DLR's Torque-Controlled Light Weight Robot III - Are We Reaching the Technological Limits Now? ICRA 2002: 1710-1716 - [c2]Gerd Hirzinger, Norbert Sporer, Markus Schedl, Jörg Butterfaß, Markus Grebenstein:
Torque-controlled Light Weight Arms and Articulated Hands - Do We Reach Technological Limits Now?. ISER 2002: 21-47 - 2000
- [c1]Gerd Hirzinger, Jörg Butterfaß, Max Fischer, Markus Grebenstein, Matthias Hähnle, Hong Liu, Ingo Schäfer, Norbert Sporer, Markus Schedl, Reinhard Koeppe:
A new Generation of Light-Weight Robot Arms and Multifingered Hands. ISER 2000: 569-570
Coauthor Index
[j47] [r3] [i17] [j30] [j29] [c161] [j26] [c153] [c152] [c136] [c132] [c130] [c127] [c118] [c115] [b1] [c91] [c89] [c81] [r1] [c69] [e5] [j14] [j10] [c54] [c45] [c42] [j7] [j6] [c39] [c36] [c34] [e2] [c32] [c30] [c27] [c26] [c25] [c24] [c23] [j4] [j3] [c20] [c19] [c17] [c16] [c15] [c14] [c13] [c12] [c11] [c10] [c9] [c8] [c7] [c6] [c5] [c4]
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2025-03-21 02:15 CET by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
