A recommendation algorithm based on local principle component analysis in mobile wireless sensor networks

• Published in: 2022 IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers (IPEC) pp. 318 - 321
• Main Author: Lu, Shiwei
• Format: Conference Proceeding
• Language: English
• Published: IEEE 14.04.2022
• Subjects: Costs; Dimensionality reduction; Fault tolerance; Fault tolerant systems; local principle component analysis; Micromechanical devices; mobile sensor networks; recommendation model; Sensor phenomena and characterization; Wireless sensor networks
• DOI: 10.1109/IPEC54454.2022.9777602

Modern technological advances have created low-cost, low-power, multi-functional micro sensing devices, which can form a network of thousands of sensors distributed in a wide area After data collection, processing and analysis, sensor networks can obtain information at any time and anywhere, so as to become a part of intelligent environment In a wide range of applications, sensor networks have innovated the sensing function This is because of its reliability, accuracy, flexibility, cost performance, and ease of use The data detected and collected by intelligent sensors may involve machine failures, earthquakes, floods, and signs of terrorist attacks The functions of sensor networks are: collecting information, processing information, monitoring the environment, which can be used for military or civil. Sensor network is a comprehensive technology based on wireless communication, digital electronics, MEMS and so on According to the high dimensionality and sparsity of rating matrix in traditional collaborative filtering recommendation system, a new recommendation model based on Local Principle Component Analysis is proposed in mobile wireless sensor networks to make dimension reduction for different subject genre respectively, and remainsthe real interested users in one specific subject of the web pages.