{"title":"基于云计算的农业产销信息推荐系统的设计与实现","authors":"Huang Haiyan, C. Tao","doi":"10.1109/ICICTA.2015.99","DOIUrl":null,"url":null,"abstract":"Our agricultural face: agricultural production is dispersed, agricultural consumption is diversified, and connection and docking are poor between small-scale production and market. We propose the agricultural marketing information recommendation system based on cloud computing in order to provide accurate recommendations for farmers. The main function modules include information acquisition and preprocessing module, user interest module based on explicit and implicit build, recommendation algorithm module based on a combination of BP neural network and SOM neural network. System implementation results show that recommendation result is accurate, the system operate normally and can achieve good economic benefits. We can achieve the desired design objectives.","PeriodicalId":231694,"journal":{"name":"2015 8th International Conference on Intelligent Computation Technology and Automation (ICICTA)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2015-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Design and Implementation of Agricultural Production and Market Information Recommendation System Based on Cloud Computing\",\"authors\":\"Huang Haiyan, C. Tao\",\"doi\":\"10.1109/ICICTA.2015.99\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Our agricultural face: agricultural production is dispersed, agricultural consumption is diversified, and connection and docking are poor between small-scale production and market. We propose the agricultural marketing information recommendation system based on cloud computing in order to provide accurate recommendations for farmers. The main function modules include information acquisition and preprocessing module, user interest module based on explicit and implicit build, recommendation algorithm module based on a combination of BP neural network and SOM neural network. System implementation results show that recommendation result is accurate, the system operate normally and can achieve good economic benefits. We can achieve the desired design objectives.\",\"PeriodicalId\":231694,\"journal\":{\"name\":\"2015 8th International Conference on Intelligent Computation Technology and Automation (ICICTA)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-06-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 8th International Conference on Intelligent Computation Technology and Automation (ICICTA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICICTA.2015.99\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 8th International Conference on Intelligent Computation Technology and Automation (ICICTA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICICTA.2015.99","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Design and Implementation of Agricultural Production and Market Information Recommendation System Based on Cloud Computing
Our agricultural face: agricultural production is dispersed, agricultural consumption is diversified, and connection and docking are poor between small-scale production and market. We propose the agricultural marketing information recommendation system based on cloud computing in order to provide accurate recommendations for farmers. The main function modules include information acquisition and preprocessing module, user interest module based on explicit and implicit build, recommendation algorithm module based on a combination of BP neural network and SOM neural network. System implementation results show that recommendation result is accurate, the system operate normally and can achieve good economic benefits. We can achieve the desired design objectives.