Current challenges and visions in music recommender systems research

M Schedl, H Zamani, CW Chen, Y Deldjoo… - International Journal of …, 2018 - Springer
Music recommender systems (MRSs) have experienced a boom in recent years, thanks to
the emergence and success of online streaming services, which nowadays make available …

Characterizing context-aware recommender systems: A systematic literature review

NM Villegas, C Sánchez, J Díaz-Cely… - Knowledge-Based …, 2018 - Elsevier
Context-aware recommender systems leverage the value of recommendations by exploiting
context information that affects user preferences and situations, with the goal of …

Enhanced human activity recognition based on smartphone sensor data using hybrid feature selection model

N Ahmed, JI Rafiq, MR Islam - Sensors, 2020 - mdpi.com
Human activity recognition (HAR) techniques are playing a significant role in monitoring the
daily activities of human life such as elderly care, investigation activities, healthcare, sports …

From action to activity: sensor-based activity recognition

Y Liu, L Nie, L Liu, DS Rosenblum - Neurocomputing, 2016 - Elsevier
As compared to actions, activities are much more complex, but semantically they are more
representative of a human׳ s real life. Techniques for action recognition from sensor …

A bayesian framework for learning rule sets for interpretable classification

T Wang, C Rudin, F Doshi-Velez, Y Liu… - Journal of Machine …, 2017 - jmlr.org
We present a machine learning algorithm for building classifiers that are comprised of a
small number of short rules. These are restricted disjunctive normal form models. An …

Improving content-based and hybrid music recommendation using deep learning

X Wang, Y Wang - Proceedings of the 22nd ACM international …, 2014 - dl.acm.org
Existing content-based music recommendation systems typically employ a\textit {two-stage}
approach. They first extract traditional audio content features such as Mel-frequency cepstral …

Action2Activity: recognizing complex activities from sensor data

Y Liu, L Nie, L Han, L Zhang, DS Rosenblum - arXiv preprint arXiv …, 2016 - arxiv.org
As compared to simple actions, activities are much more complex, but semantically
consistent with a human's real life. Techniques for action recognition from sensor generated …

Music recommender systems

M Schedl, P Knees, B McFee, D Bogdanov… - Recommender systems …, 2015 - Springer
This chapter gives an introduction to music recommender systems research. We highlight
the distinctive characteristics of music, as compared to other kinds of media. We then …

Music information retrieval: Recent developments and applications

M Schedl, E Gómez, J Urbano - Foundations and Trends® in …, 2014 - nowpublishers.com
We provide a survey of the field of Music Information Retrieval (MIR), in particular paying
attention to latest developments, such as semantic auto-tagging and user-centric retrieval …

AI-based mobile context-aware recommender systems from an information management perspective: Progress and directions

M del Carmen Rodríguez-Hernández, S Ilarri - Knowledge-Based Systems, 2021 - Elsevier
Abstract In the Artificial Intelligence (AI) field, and particularly within the area of Machine
Learning (ML), recommender systems have attracted significant research attention. These …