A table of publications on multimedia recommender systems, in particular recommender systems that leverage multimedia content. This page will be periodically updated to include the most recent works. Please contact us if your work is not in the list.
The table serves as overview and extension of the works discussed in the following survey. Please consider citing it if you used the survey.
@article{deldjoo2020recommender,
title={Recommender systems leveraging multimedia content},
author={Deldjoo, Yashar and Schedl, Markus and Cremonesi, Paolo and Pasi, Gabriella},
journal={ACM Computing Surveys (CSUR)},
volume={53},
number={5},
pages={1--38},
year={2020},
publisher={ACM New York, NY, USA}
}
| Year | Authors | Title | Venue | Target Item | Paper | Code | Data/Source |
|---|---|---|---|---|---|---|---|
| 2019 | Smith et al. | Towards a Hybrid RecommendationSystem for a Sound Library. | IUI |  |
Link | -- | EarSketch WordNet FreeSound |
| 2016 | Ostuni et al. | Sound and Music Recommendation with Knowledge Graphs. | TIST | |
Link | -- | Songfacts Last.fmFreeSound |
| 2015 | Oramas et al. | A Semantic Hybrid Approach for Sound Recommendation. | WWW | |
Link | -- | DBpedia [WordNet] |
| Year | Authors | Title | Venue | Target Item | Link | Code | Data |
|---|---|---|---|---|---|---|---|
| 2019 | Vall et al. | Feature-Combination Hybrid Recommender Systems for Automated Music Playlist Continuation. | UMUAI |  |
Link | Link | DS_name |
| 2017 | Oramas et al. | A Deep Multimodal Approach for Cold-start Music Recommendation.. | DLRS | |
Link | Link | Million Song Dataset (MSD) |
| 2015 | Liang et al. | Content-Aware Collaborative Music Recommendation Using Pre-trained Neural Networks. | ISMIR | |
Link | Link1 Link2 |
Million Song Dataset (MSD) |
| 2014 | Shah et al. | ADVISOR: Personalized Video Soundtrack Recommendation by Late Fusion with Heuristic Rankings. | ACM MM | |
Link | -- | Last.fm FourSquare (NA) GeoVid app |
| 2014 | Wang et al. | Improving Content-based and Hybrid Music Recommendation Using Deep Learning. | ACM MM | |
Link | Echo Nest Taste 7digital |
|
| 2013 | Van den Oord et al. | Deep Content-based Music Recommendation. | NIPS | |
Link | -- | Million Song Dataset (MSD) |
| 2013 | Kaminskas et al. | Location-aware music recommendation using auto-taggingand hybrid matching. | RecSys | |
Link | -- | |
| 2011 | McFee et al. | The Natural Language of Playlists. | ISMIR | |
Link | MSD Echo Nest Last.fm Art of the Mix(AotM) |
|
| 2010 | Bu et al. | Music recommendation by unified hypergraph: combining social media information and music content. | ACM MM | |
Link | -- | Last.fm |
| 2009 | Shao et al. | Music recommendation based on acoustic features and user access patterns. | ACM Tr. ASLP | |
Link | -- | New Wisdom (NA) |
| 2008 | Yoshii et al. | An Efficient Hybrid Music Recommender System Using an Incrementally Trainable Probabilistic Generative Model. | IEEE Tr. ASLP | |
Link | -- | DS_name |
| Year | Authors | Title | Venue | Target Item | Link | Code | Data |
|---|---|---|---|---|---|---|---|
| 2018 | Niu et al. | Neural Personalized Ranking for Image Recommendation. | WSDM |  |
Link | Flickr YFCC100M | |
| 2018 | Wen et al. | Visual Background Recommendation for Dance Performances Using Deep Matrix Factorization. | TOMCCAP |  |
Link | -- | |
| 2017 | Peska et al. | Towards Recommender Systems for Police Photo Lineup. | DLRS* |  |
Link | Link | Data |
| 2017 | Rawat et al. | ClickSmart: A Context-Aware Viewpoint Recommendation System for Mobile Photography. | IEEE Tr. CSVT |  |
Link | -- | FlickerAPI |
| 2016 | Nguyen et al. | NowAndThen: a social network-based photo recommendation tool supporting reminiscence. | MUM | |
Link | -- | Oxford Building DS |
| 2015 | Geng et al. | Learning Image and User Features for Recommendation in Social Networks. | ICCV |  |
Link | Link | Data (Pinterest) |
| 2014 | Wu et al. | Learning to personalize trending image search suggestion. | SIGIR |  |
Link | Search Logs | |
| 2013 | Albanese et al. | A multimedia recommender system | TOIT |  |
Link | -- | Uffizi Gallery (NA) ImdbAPI |
| 2013 | Bartolini et al. | Recommending multimedia objects in cultural heritage applications. | ICIP | |
Link | -- | Manual-buit repo about Paestum (NA) |
| 2011 | Bourke et al. | The social camera: a case-study in contextual image recommendation. | IUI | |
Link | -- | NA |
| 2010 | Cui et al. | Multiple feature fusion for social media applications. | SIGMOD | |
Link | FlickerAPI | |
| 2010 | Albanese et al. | A multimedia recommender integrating object features and user behavior. | MTAP | |
Link | -- | Uffizi Gallery (NA) |
| 2008 | Boutemedjet et al. | A graphical model for context-aware visual content recommendation. | IEEE Tr. MM |  |
Link | -- | WashingtonUni. ImageDB |
| 2006 | Boutemedjet et al. | A generative graphical model for collaborative filtering of visual content. | ICDM | |
Link | -- | WashingtonUni. ImageDB |
| Year | Title | Target Item | Venue | Code | Data |
|---|---|---|---|---|---|
| 2019 | Movie Genome: Alleviating New Item Cold Start in Movie Recommendation. |  |
MTAP | Code | MMTF-14K |
| 2018 | Exploiting Visual Contents in Posters and Still Frames for Movie Recommendation. | |
IEEE Access | IMDB | |
| 2018 | Using visual features and latent factors for movie recommendation. | |
CBRecSys | ||
| 2018 | Using Visual Features based on MPEG-7 and Deep Learning for Movie Recommendation. | |
IJMIR | Mise-en-Scène DS: MPEG-7 + CNN | |
| 2018 | Audio-visual encoding of multimedia content for enhancing movie recommendations. | |
RecSys | MMTF-14K | |
| 2016 | Latent factor representations for cold-start video recommendation. | |
RecSys | 1:Video Emotion DS (Av. upon Req.) 2: Amazon Product |
|
| 2016 | Content-based video recommendation system based on stylistic visual features. | |
JoDS | ||
| 2013 | Affective recommendation of movies based on selected connotative features. | |
RecSys | Gratest film scenes | |
| 2013 | VideoTopic: Content-Based Video Recommendation Using a Topic Model. | |
MTAP | IMDB + YouTube |
| Year | Authors | Title | Target Item | Venue | Code | Data/Resources |
|---|---|---|---|---|---|---|
| 2018 | Ma et al. | LGA: latent genre aware micro-video recommendation on social media. |  |
MTAP | -- | Twitter Streaming API |
| 2014 | Cui et al. | What videos are similar with you?: Learning a common attributed representation for video recommendation | |
ACM MM | -- | Tencent Weibo* |
| 2013 | Deng et al. | Personalized video recommendation based on cross-platform user modeling. | |
ICME | -- | Google+,YouTube |
| 2012 | Zhao et al. | On video recommendation over social network. | |
MMM | -- | Facebook / Aspel+WordNet |
| 2012 | Zhao et al. | Personalized video recommendation based on viewing history with the study on youtube. | |
ICIMCS | -- | YouTube |
| 2011 | Mei et al. | Contextual video recommendation by multimodal relevance and user feedback. | |
ACM TOIS | -- | MSN Video |
| 2007 | Yang et al. | Online video recommendation based on multimodal fusion and relevance feedback. | |
CIVR | -- | MSN Soapbox (NA) |
*Tencent Weibo is a Twitter-style social media in China.
For questions, please feel free to contact us at deldjooy@acm.org.
- Yashar Deldjoo deldjooy@acm.org , yashar.deldjoo@poliba.it
- Markus Schedl markus.schedl@jku.at
- Paolo Cremonesi paolo.cremonesi@polimi.it
- Gabriella Pasi gabriella.pasi@unimib.it