| Time |
Session |
Speaker(s) / Description |
| 08:55 AM - 09:00 AM CDT |
Intro and Welcome |
Organizers |
| 09:00 AM - 09:45 AM CDT |
Keynote Talk # 1 - What can we learn from analyzing streaming music data? |
Eva Zangerle |
| 09:45 AM - 10:00 AM CDT |
Accepted Paper # 1. Entity and Event Topic Extraction from Podcast Episode Title and Description Using Entity Linking (Amazon Music) |
Christian Siagian and Amina Shabbeer. |
| 10:00 AM - 10:15 AM CDT |
Accepted Paper # 2. MEMER - Multimodal Encoder for Multi-signal Early-stage Recommendations (ShareChat) |
Mohit Agarwal, Srijan Saket and Rishabh Mehrotra. |
| 10:15 AM - 10:30 AM CDT |
Accepted Paper # 3. Deep Neural Network with LinUCB: A Contextual Bandit Approach for Personalized Recommendation (Disney Streaming) |
Qicai Shi, Feng Xiao, Douglas Pickard, Inga Chen and Liang Chen. |
| 10:30 AM - 11:00 AM CDT |
Break |
|
| 11:00 - 11:45 am CDT |
Keynote Talk # 2 - Powering Personalized Binge-Watching Recommendations: A Journey of Realtime Multi-Interest Based Retrieval |
Jaya Kawale |
| 11:45 AM - 12:00 noon CDT |
Accepted Paper # 4. Improve retrieval of regional titles in streaming services with dense retrieval (Amazon - Prime Video) |
Bhargav Upadhyay, Tejas Khairnar and Anup Kotalwar. |
| 12:00 noon - 12:30 PM CDT |
Invited Talk # 1. Deep Downsampling (Netflix) |
|
| 12:30 - 1:30 pm CDT |
Lunch Break |
|
| 1:30 - 2:15 pm CDT |
Keynote Talk # 3 - Recent Advances in Conversational Recommender Systems |
Laurent Charlin |
| 2:15 - 2:30 pm CDT |
Accepted Paper # 5 - A Probabilistic Position Bias Model for Short-Video Feeds (ShareChat) |
Olivier Jeunen |
| 2:30 - 3:00 pm CDT |
Invited Talk # 2 |
|
| 3:00 -3:30 pm CDT |
Break |
|
| 3:30 - 4:15 pm CDT |
Keynote Talk # 4. TBD |
Ben Carterette |
| 4:15 pm - 4:45 pm CDT |
Invited Talk - When Hollywood Meets AI: The Use of Machine Learning in Creative Industries |
Lan Luo |
| 4:45 - 5:00 pm CDT
| Closing Remarks
| Organizers
|