基于概率主题的物品万维网资源管理机制  

WEB OF THINGS RESOURCE MANAGEMENT BASED ON PROBABILISTIC TOPIC MODEL

作　　者：李养群[1,2] Li Yangqun(School of Internet of Things,Nanjing University of Posts and Telecommunications,Nanjing 210003,Jiangsu,China;Key Lab of Broadband Wireless Communication and Sensor Network Technology,Ministry of Education,Nanjing University of Posts and Telecommunications,Nanjing 210003,Jiangsu,China)

机构地区：[1]南京邮电大学物联网学院,江苏南京210003 [2]南京邮电大学江苏省宽带无线通信与物联网重点实验室,江苏南京210003

出　　处：《计算机应用与软件》2024年第8期84-91,共8页Computer Applications and Software

基　　金：国家自然科学基金项目(61972211)。

摘　　要：针对物品万维网(WoT)资源管理复杂度高、效率低的问题,提出一种基于概率主题模型的WoT资源智能化管理机制。从资源描述中自动提取主题信息;利用分类算法对该主题进行分类;根据分类结果将资源发布在WoT网关构建的P2P网络中。仿真实验表明,该方法与基于文本及语义的方法相比,具有较高的管理效率以及准确率,同时,基于相同主题的资源分布式存储也提高了应用的可用性。最后,给出一个WoT资源优化管理的实例分析。Aimed at the problems of high complexity and low efficiency of existing technology for Web of Things(WoT)resources management,an intelligent WoT resources management mechanism based on probabilistic topic model is proposed.This mechanism automatically extracted topic information from the WoT resource description,used machine learning algorithms to classify the topic,and published the resources in the P2P network constructed by the WoT gateway based on the classification results.Simulation results show that this mechanism has higher management efficiency and accuracy than text-based and semantic-based methods.Distributed storage of resources based on the topic also improves the usability of the application.An example of this mechanism in the intelligent management of WoT resources was given.

关 键 词：物品万维网 智能化资源管理 概率主题模型 资源发现 机器学习 

分 类 号：TP3[自动化与计算机技术—计算机科学与技术]