Anu Agarwal
Biographic Data
| ID | 10055854 |
|---|---|
| NAME | Anu Agarwal |
| GIVEN NAMES | Anu |
| FAMILY NAME | Agarwal |
| SIGNATURE | AGARWAL A |
| AFFILIATIONS | Samsung (India) |
| ORCID | 0000-0002-2619-2616 |
| VERIFIED | Yes |
| TOTAL WORKS | 1 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 1 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2022 |
| LATEST PUBLICATION YEAR | 2022 |
| H-INDEX | 0 |
Potent Real-Time Recommendations Using Multimodel Contextual Reinforcement Learning
Widespread digitalization has led to almost all utilities and services thrive on an online medium. A real-time, personalized, and trend grasping recommendation system is necessary to enhance user experience and boost business on E-commerce platforms. We propose the Multimodel Contextual Reinforcement Learning (MMCR) constituting three novel features for real-time and customized recommendations. The first feature is user-item interactive state emb…
No prominent works on this page.
Potent Real-Time Recommendations Using Multimodel Contextual Reinforcement Learning
Widespread digitalization has led to almost all utilities and services thrive on an online medium. A real-time, personalized, and trend grasping recommendation system is necessary to enhance user experience and boost business on E-commerce platforms. We propose the Multimodel Contextual Reinforcement Learning (MMCR) constituting three novel features for real-time and customized recommendations. The first feature is user-item interactive state emb…
Artificial Intelligence (1 work) · Caching and Content Delivery (1 work) · Computer Science (1 work) · Human Mobility and Location-Based Analysis (1 work) · Machine learning (1 work) · Novelty (1 work) · Randomness (1 work) · Recommender system (1 work) · Recommender Systems and Techniques (1 work) · Reinforcement learning (1 work)