Yuyu Yin
Biographic Data
| ID | 10055574 |
|---|---|
| NAME | Yuyu Yin |
| GIVEN NAMES | Yuyu |
| FAMILY NAME | Yin |
| SIGNATURE | YIN Y |
| AFFILIATIONS | Hangzhou Dianzi University |
| ORCID | 0000-0001-7565-4111 |
| VERIFIED | Yes |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 3 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2022 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 0 |
Multitask-Based Self-Supervised Learning for Recommendation in Social Systems
In computational social systems, recommendation functionality plays a pivotal role in influencing user behavior, enhancing user experience, and driving engagement. To help recommendation functionality to better suggest relevant content or items, the social platforms usually utilize large-scale knowledge discovery techniques to analyze trends in user interactions and extract patterns from large datasets. Click-through rate (CTR) prediction is cruc…
The Deep Features and Attention Mechanism-Based Method to Dish Healthcare Under Social IoT Systems
Many mobile apps of social Internet of Things (sIOT) systems can help us record and share daily events, such as health and sport events. In fact, healthy diet recognition is an important and challenging problem in dish health assessment. Via the collection and monitoring of data pertaining to our daily diet, we can work in collaborative ways to achieve dish image annotation based on sIOT systems to enhance deep features. To this end, this article…
Exploiting User Preferences for Multiscenarios in Query-Less Search
Online travel platforms (OTPs), for example, booking.com, Ctrip.com, and Fliggy, deliver travel experiences to online users by providing travel-related products. Hotel recommendation is significantly important for OTPs since hotel bookings account for almost half of the travel expenses and hotel products generate more than half of OTP’s revenues. More than 58% Fliggy users may choose to use query-less hotel searches to find candidate hotels, wher…
No prominent works on this page.
The Deep Features and Attention Mechanism-Based Method to Dish Healthcare Under Social IoT Systems
Many mobile apps of social Internet of Things (sIOT) systems can help us record and share daily events, such as health and sport events. In fact, healthy diet recognition is an important and challenging problem in dish health assessment. Via the collection and monitoring of data pertaining to our daily diet, we can work in collaborative ways to achieve dish image annotation based on sIOT systems to enhance deep features. To this end, this article…
Exploiting User Preferences for Multiscenarios in Query-Less Search
Online travel platforms (OTPs), for example, booking.com, Ctrip.com, and Fliggy, deliver travel experiences to online users by providing travel-related products. Hotel recommendation is significantly important for OTPs since hotel bookings account for almost half of the travel expenses and hotel products generate more than half of OTP’s revenues. More than 58% Fliggy users may choose to use query-less hotel searches to find candidate hotels, wher…
Multitask-Based Self-Supervised Learning for Recommendation in Social Systems
In computational social systems, recommendation functionality plays a pivotal role in influencing user behavior, enhancing user experience, and driving engagement. To help recommendation functionality to better suggest relevant content or items, the social platforms usually utilize large-scale knowledge discovery techniques to analyze trends in user interactions and extract patterns from large datasets. Click-through rate (CTR) prediction is cruc…
Computer Science (3 works) · Artificial Intelligence (2 works) · Computer security (2 works) · Machine learning (2 works) · Recommender Systems and Techniques (2 works) · World Wide Web (2 works) · Advanced Chemical Sensor Technologies (1 work) · Advanced Text Analysis Techniques (1 work) · Business (1 work) · Click-through rate (1 work)