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20172024
most citedA Deep Multimodal Approach for Cold-start Music Recommendation

80 citations

Showing cs.IRShow all

5 papers · 1 filter

cs.IR202413 cited

It's Not You, It's Me: The Impact of Choice Models and Ranking Strategies on Gender Imbalance in Music Recommendation

Andres Ferraro, Michael D. Ekstrand, Christine Bauer

As recommender systems are prone to various biases, mitigation approaches are needed to ensure that recommendations are fair to various stakeholders. One particular concern in musi…

cs.IR20206 cited

Multimodal Metric Learning for Tag-based Music Retrieval

Minz Won, Sergio Oramas, Oriol Nieto +2

Tag-based music retrieval is crucial to browse large-scale music libraries efficiently. Hence, automatic music tagging has been actively explored, mostly as a classification task,…

cs.IR20203 cited

Efficient Personalized Community Detection via Genetic Evolution

Zheng Gao, Chun Guo, Xiaozhong Liu

Personalized community detection aims to generate communities associated with user need on graphs, which benefits many downstream tasks such as node recommendation and link predict…

cs.IR201714 cited

Predicting Session Length in Media Streaming

Theodore Vasiloudis, Hossein Vahabi, Ross Kravitz +1

Session length is a very important aspect in determining a user's satisfaction with a media streaming service. Being able to predict how long a session will last can be of great us…

cs.IR201780 cited

A Deep Multimodal Approach for Cold-start Music Recommendation

Sergio Oramas, Oriol Nieto, Mohamed Sordo +1

An increasing amount of digital music is being published daily. Music streaming services often ingest all available music, but this poses a challenge: how to recommend new artists…