家电科技Issue(z1)：120-124,5.DOI:10.19784/j.cnki.issn1672-0172.2024.99.025
基于知识塔群的智慧家庭场景自生成技术研究
Self-generation of smart home scenarios based on knowledge tower clusters
杜永杰 1王杰 2陈天璐 3马晓然1
作者信息
- 1. 青岛海尔科技有限公司 山东 青岛 266100||数字家庭网络国家工程研究中心 山东 青岛 266100||山东省智慧家庭人工智能与自然交互研究重点实验室 山东 青岛 266100
- 2. 青岛海尔科技有限公司 山东 青岛 266100||数字家庭网络国家工程研究中心 山东 青岛 266100
- 3. 青岛海尔科技有限公司 山东 青岛 266100||山东省智慧家庭人工智能与自然交互研究重点实验室 山东 青岛 266100
- 折叠
摘要
Abstract
The rise of large AI models is rapidly reshaping the smart home sector.However,these systems often struggle with scattered knowledge,scene adaptability,and personalized services.To overcome these hurdles,this paper presents a smart home scenario self-generation technique based on a knowledge tower cluster.We design a layered appliance ontology and integrate large models using a synergistic optimization approach rooted in the tower cluster's knowledge graph,bolstering model reliability and generalization in smart homes.By capturing multi-dimensional inputs from users,devices,environments,and spaces,we create precise user profiles and autonomous scene organizers with graph neural networks and transfer learning.This enhances task adaptability and self-learning,enabling proactive,customized user experiences.Testing reveals that our approach achieves a scenario generation accuracy of over 95％.关键词
知识图谱/增量学习/意图识别/场景生成Key words
Knowledge graph/Incremental learning/Intent recognition/Scene generation分类
信息技术与安全科学引用本文复制引用
杜永杰,王杰,陈天璐,马晓然..基于知识塔群的智慧家庭场景自生成技术研究[J].家电科技,2024,(z1):120-124,5.
