Sha Zhao
Biographic Data
| ID | 10054022 |
|---|---|
| NAME | Sha Zhao |
| GIVEN NAMES | Sha |
| FAMILY NAME | Zhao |
| SIGNATURE | ZHAO S |
| AFFILIATIONS | Zhejiang University of Science and Technology |
| ORCID | 0000-0003-4628-5198 |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 2 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2021 |
| LATEST PUBLICATION YEAR | 2023 |
| H-INDEX | 0 |
Unsupervised Domain Adaptation for Crime Risk Prediction Across Cities
Crime risk prediction is crucial for city safety and residents’ life quality. However, without labeled data, it is challenging to predict crime risk in cities. Due to municipal regulations and maintenance costs, it is not trivial for many cities to collect high-quality labeled crime data. In particular, some cities have lots of labeled data while others may have few. It has been possible to develop a crime prediction model for a city without labe…
Player Behavior Modeling for Enhancing Role-Playing Game Engagement
Role-playing games (RPGs) are one of the most exciting and most rapidly expanding genres of online games. Virtual characters that are not controlled by players, have become an integral part, which helps to advance narratives of RPGs. Believable characters can enhance game engagement and further improve player retention. However, game players easily find that most characters' behaviors are limited and improbable, resulting in a less meaningful gam…
No prominent works on this page.
Player Behavior Modeling for Enhancing Role-Playing Game Engagement
Role-playing games (RPGs) are one of the most exciting and most rapidly expanding genres of online games. Virtual characters that are not controlled by players, have become an integral part, which helps to advance narratives of RPGs. Believable characters can enhance game engagement and further improve player retention. However, game players easily find that most characters' behaviors are limited and improbable, resulting in a less meaningful gam…
Unsupervised Domain Adaptation for Crime Risk Prediction Across Cities
Crime risk prediction is crucial for city safety and residents’ life quality. However, without labeled data, it is challenging to predict crime risk in cities. Due to municipal regulations and maintenance costs, it is not trivial for many cities to collect high-quality labeled crime data. In particular, some cities have lots of labeled data while others may have few. It has been possible to develop a crime prediction model for a city without labe…
Computer Science (2 works) · Artificial Intelligence (1 work) · Artificial Intelligence in Games (1 work) · Crime Patterns and Interventions (1 work) · Data science (1 work) · Digital Games and Media (1 work) · Domain adaptation (1 work) · Educational Games and Gamification (1 work) · Engineering (1 work) · Game art design (1 work)