CITATION — REFERENCE ENTRY
Current challenges and visions in music recommender systems research — International Journal of Multimedia Information Retrieval
- Key
- schedl2018-music-recsys
- Authors
- Schedl, Markus; Zamani, Hamed; Chen, Ching-Wei; Deldjoo, Yashar; Elahi, Mehdi
- Issued
- 2018
- Type
- article-journal
- Container
- International Journal of Multimedia Information Retrieval
- Volume
- 7
- Issue
- 2
- Pages
- 95-116
Raw CSL JSON
{
"DOI": "10.1007/s13735-018-0154-2",
"URL": "https://arxiv.org/abs/1710.03208",
"page": "95-116",
"type": "article-journal",
"issue": "2",
"title": "Current challenges and visions in music recommender systems research",
"author": [
{
"given": "Markus",
"family": "Schedl"
},
{
"given": "Hamed",
"family": "Zamani"
},
{
"given": "Ching-Wei",
"family": "Chen"
},
{
"given": "Yashar",
"family": "Deldjoo"
},
{
"given": "Mehdi",
"family": "Elahi"
}
],
"issued": {
"date-parts": [
[
2018
]
]
},
"volume": "7",
"container-title": "International Journal of Multimedia Information Retrieval"
}
Claims
-
Streaming services have driven growth in music recommender systems; a key research challenge is building and evaluating strategies that go beyond user-item interactions and content descriptors to address listener needs, preferences, and intentions.
"Music recommender systems (MRS) have experienced a boom in recent years, thanks to the emergence and success of online streaming services, which nowadays make available almost all music in the world at the user's fingertip. [...] In particular when it comes to build, incorporate, and evaluate recommendation strategies that integrate information beyond simple user--item interactions or content-based descriptors, but dig deep into the very essence of listener needs, preferences, and intentions, MRS research becomes a big endeavor and related publications quite sparse."
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