首页> 外文会议>Semantics, Knowledge and Grid, 2009. SKG 2009 >Based on the Reinforcement learning Association Rules Recommendation study
【24h】

Based on the Reinforcement learning Association Rules Recommendation study

机译:基于强化学习的关联规则推荐研究

获取原文

摘要

Reinforcement learning is an important method of machine learning. This paper using the graph theory to express varieties of knowledge points, which their's relationship is expressed by the graph of topological graph. Applied the Technology of association rule Recommendation to deal with the relationship between these knowledge points, give the corresponding of the recommendation work flow chart. In the paper data tables used to store the knowledge points, the algorithm to demonstrate the technical of association rule Recommendation feasibility and rationality.
机译:强化学习是机器学习的重要方法。本文利用图论来表达知识点的多样性,它们之间的关系用拓扑图的图表示。应用关联规则推荐技术处理这些知识点之间的关系,给出相应的推荐工作流程图。在用于存储知识点的纸质数据表中,该算法证明了关联规则技术的建议可行性和合理性。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号