Current challenges and visions in music recommender systems research
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 …
the emergence and success of online streaming services, which nowadays make available …
Characterizing context-aware recommender systems: A systematic literature review
Context-aware recommender systems leverage the value of recommendations by exploiting
context information that affects user preferences and situations, with the goal of …
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
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 …
daily activities of human life such as elderly care, investigation activities, healthcare, sports …
From action to activity: sensor-based activity recognition
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 …
representative of a human׳ s real life. Techniques for action recognition from sensor …
A bayesian framework for learning rule sets for interpretable classification
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 …
small number of short rules. These are restricted disjunctive normal form models. An …
Improving content-based and hybrid music recommendation using deep learning
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 …
approach. They first extract traditional audio content features such as Mel-frequency cepstral …
Action2Activity: recognizing complex activities from sensor data
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 …
consistent with a human's real life. Techniques for action recognition from sensor generated …
Music recommender systems
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 …
the distinctive characteristics of music, as compared to other kinds of media. We then …
Music information retrieval: Recent developments and applications
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 …
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 …
Learning (ML), recommender systems have attracted significant research attention. These …