Abstract
Personalization services enable Internet users to benefit from tailored recommended content at their finger tips. Our interest in
this contribution lies in video recommendation within the fitness
domain to support an active lifestyle. We present ’Fitness that Fits’, a preliminary platform for workout video recommendation, which benefits from the Youtube-8M labeled dataset and its rich variety of categorized video labels, thereby enabling fitness workout video recommendations predicated on the users’ preferences and their recent viewing behavior. The proposed model also incorporates an approach to produce diversified recommendations and foster the practice of distinct fitness activities based on like-minded users’ information. An initial experimental study shows the trade-offs of the hybrid approach considered.
this contribution lies in video recommendation within the fitness
domain to support an active lifestyle. We present ’Fitness that Fits’, a preliminary platform for workout video recommendation, which benefits from the Youtube-8M labeled dataset and its rich variety of categorized video labels, thereby enabling fitness workout video recommendations predicated on the users’ preferences and their recent viewing behavior. The proposed model also incorporates an approach to produce diversified recommendations and foster the practice of distinct fitness activities based on like-minded users’ information. An initial experimental study shows the trade-offs of the hybrid approach considered.
| Original language | English |
|---|---|
| Number of pages | 6 |
| Publication status | Published - 2 Oct 2018 |
| Event | 12th ACM Conference on Recommender Systems - Vancouver, Canada Duration: 2 Oct 2018 → 7 Oct 2018 https://recsys.acm.org/recsys18/ |
Conference
| Conference | 12th ACM Conference on Recommender Systems |
|---|---|
| Abbreviated title | RECSYS 2018 |
| Country | Canada |
| City | Vancouver |
| Period | 2/10/18 → 7/10/18 |
| Internet address |
Structured keywords
- Jean Golding
Keywords
- Personalized Wellbeing
- Preference Modeling
- Diversity
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Cite this
Ezin, E., Kim, E., & Palomares Carrascosa, I. (2018). 'Fitness that Fits': - A Prototype Model for Workout Video Recommendation. Paper presented at 12th ACM Conference on Recommender Systems, Vancouver, Canada.