• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议>Distributed computing and artificial intelligence. >Analysis of Sequential Events for the Recognition of Human Behavior Patterns in Home Automation Systems
【24h】

Analysis of Sequential Events for the Recognition of Human Behavior Patterns in Home Automation Systems

机译：识别家庭自动化系统中人类行为模式的顺序事件分析

获取原文
获取原文并翻译 | 示例
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Learning users' frequent patterns is very useful to develop real human-centered environments. By analyzing the occurrences of events over time in a home automation system, it's possible to find periodic patterns based on action-time relationships. However, the human behavior could be better defined if it's related to chained actions, creating action-action relationships. This work presents IntelliDomo's learning layer, a data mining approach based on ontologies and production rules that aims to achieve those objectives. This module is able to acquire users' habits and automatically generate production rules for behavior patterns to anticipate the user's periodic actions. The learning layer includes new features looking for the adaptability and personification of the environment.
机译：学习用户的频繁模式对于开发以人为本的真实环境非常有用。通过分析家庭自动化系统中随时间变化的事件发生，可以根据动作时间关系找到周期性的模式。但是，如果人类行为与链式动作相关联，则可以更好地定义其行为，从而创建动作与动作的关系。这项工作展示了IntelliDomo的学习层，这是一种基于本体和生产规则的数据挖掘方法，旨在实现这些目标。该模块能够掌握用户的习惯，并自动生成行为模式的生产规则，以预测用户的周期性行为。学习层包括新功能，以寻找环境的适应性和个性化。

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