An Alternative-Service Recommending Algorithm Based on Semantic Similarity

被引:2
|
作者
Kun Guo [1 ]
Yonghua Li [1 ]
Yueming Lu [1 ]
机构
[1] Key Laboratory of Trustworthy Distributed Computing and Service,Ministry of Education,Beijing University of Posts and Telecommunications
关键词
activity recognition; semantic model; service recommendation; unavailable service;
D O I
暂无
中图分类号
TP391.3 [检索机];
学科分类号
081203 ; 0835 ;
摘要
With the development of the Internet of Things(Io T), people’s lives have become increasingly convenient. It is desirable for smart home(SH) systems to integrate and leverage the enormous information available from IoT. Information can be analyzed to learn user intentions and automatically provide the appropriate services. However, existing service recommendation models typically do not consider the services that are unavailable in a user’s living environment. In order to address this problem, we propose a series of semantic models for SH devices. These semantic models can be used to infer user intentions. Based on the models, we proposed a service recommendation probability model and an alternative-service recommending algorithm. The algorithm is devoted to providing appropriate alternative services when the desired service is unavailable. The algorithm has been implemented and achieves accuracy higher than traditional Hidden Markov Model(HMM). The maximum accuracy achieved is 68.3%.
引用
收藏
页码:124 / 136
页数:13
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