DaGzang:用于跨领域推服务的合成数据生成器
Luong Vuong Nguyen1, Nam D Vo1, Jason J Jung2
1Department of Artificial Intelligence, FPT University, Da Nang, Vietnam.
PeerJ. Computer science
|June 22, 2023
概括
本研究介绍了DaGzang,这是一个用于生成跨领域推系统 (CDRS) 合成数据的平台. 基于用户的协作过 (CF) 使用DaGzang实现了最佳性能.
科学领域:
- 计算机科学 计算机科学
- 人工智能的人工智能
- 推系统是一个推系统.
背景情况:
- 跨领域推系统 (CDRS) 利用跨领域的关联来改进用户建模和推.
- 在CDRS中,一个主要的挑战是缺乏特定领域的数据,这阻碍了推的产生.
- 在现实世界中,很难识别重叠的关联,这限制了CDRS的实际应用.
研究的目的:
- 介绍DaGzang,一个专门为跨领域推系统设计的合成数据生成平台.
- 解决CDRS内部特定领域的数据稀缺性挑战.
- 通过克服识别现实世界重叠协会的困难,促进CDRS的实际应用.
主要方法:
- 达格尚平台以三步循环运行:检测现实数据集之间的重叠关联,基于这些关联生成合成数据集,并评估合成数据质量.
- 来自亚马逊电子商务平台的真实世界数据集被用于实验.
- 合成数据集被集成到DakGalBi跨域推系统中,用于使用协作过 (CF) 算法进行评估.
主要成果:
- 使用合成数据集的CDRS的性能使用平均绝对误差 (MAE) 和根平均平方误差 (RMSE) 进行了评估.
- 基于用户的协作过 (CF) 在评估的方法中表现最高.
- 基于用户的CF使用DaGzang生成的10个合成数据集取得了最佳结果,MAE为0.437和RMSE为0.465.
结论:
- 达格赞平台有效地生成合成数据集,提高跨领域推系统的性能.
- 合成数据生成是解决CDRS中数据稀疏问题的可行解决方案.
- 基于用户的协作过在应用到由DaGzang平台生成的合成数据集时显示出强大的有效性.
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