Find Your Organization in MMORPGs
| Autor: | Qilin Deng, Xudong Shen, Jianrong Tao, Minghao Zhao, Runze Wu, Changjie Fan, Kai Wang |
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| Rok vydání: | 2022 |
| Předmět: |
Matching (statistics)
business.industry Computer science Core component Deep learning ComputingMilieux_PERSONALCOMPUTING Machine learning computer.software_genre Preference Artificial Intelligence Control and Systems Engineering Social system Component (UML) Graph (abstract data type) Artificial intelligence Electrical and Electronic Engineering Baseline (configuration management) business computer Software |
| Zdroj: | IEEE Transactions on Games. 14:446-455 |
| ISSN: | 2475-1510 2475-1502 |
| Popis: | Social relationships are the basis for communication and collaboration between players in many online games. In this paper, we propose a machine learning-based approach to model the relationship between players and guilds in online games. Our approach combines deep learning techniques with useful prior expert knowledge, where the core component is a graph convolutional network that is designed to utilize both social relationships and behavior preference of players. For each player in the game, the model is trained to estimate the likelihood of whether the player matches the guild, which enables rapid matching of players and guilds via recommendation. The proposed approach is evaluated on a industrial dataset collected from a popular online game, and also deployed in the game as a basic component of the social system. Experimental results show that our approach is not only intuitive but also very superior to other baseline methods. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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