{"title":"建筑材料行业推荐系统的上下文数据建模","authors":"Sutthirat Kliangklao, N. Suvonvorn","doi":"10.1109/ICSEC56337.2022.10049329","DOIUrl":null,"url":null,"abstract":"The recommendation system is one of the most important supported technologies to e-commerce that aims for recommending products or services to increase customer’s satisfaction. In this paper, we propose the method for Contextual Data Modeling as an improved version of Hybrid Filtering to introduce the context-awareness in the building and construction materials business. The recommendation along with e-commerce system are built, deployed, and tested in the real situation. The evaluation score is up to 97.8 compared to baseline.","PeriodicalId":430850,"journal":{"name":"2022 26th International Computer Science and Engineering Conference (ICSEC)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Contextual Data Modeling for Recommender System in Building and Construction Materials Business\",\"authors\":\"Sutthirat Kliangklao, N. Suvonvorn\",\"doi\":\"10.1109/ICSEC56337.2022.10049329\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The recommendation system is one of the most important supported technologies to e-commerce that aims for recommending products or services to increase customer’s satisfaction. In this paper, we propose the method for Contextual Data Modeling as an improved version of Hybrid Filtering to introduce the context-awareness in the building and construction materials business. The recommendation along with e-commerce system are built, deployed, and tested in the real situation. The evaluation score is up to 97.8 compared to baseline.\",\"PeriodicalId\":430850,\"journal\":{\"name\":\"2022 26th International Computer Science and Engineering Conference (ICSEC)\",\"volume\":\"14 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-12-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 26th International Computer Science and Engineering Conference (ICSEC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSEC56337.2022.10049329\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 26th International Computer Science and Engineering Conference (ICSEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSEC56337.2022.10049329","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Contextual Data Modeling for Recommender System in Building and Construction Materials Business
The recommendation system is one of the most important supported technologies to e-commerce that aims for recommending products or services to increase customer’s satisfaction. In this paper, we propose the method for Contextual Data Modeling as an improved version of Hybrid Filtering to introduce the context-awareness in the building and construction materials business. The recommendation along with e-commerce system are built, deployed, and tested in the real situation. The evaluation score is up to 97.8 compared to baseline.
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