E. Phaisangittisagul, Y. Koobkrabee, K. Wirojborisuth, T. Ratanasrimetha, S. Aummaro
{"title":"Target Advertising Classification using Combination of Deep Learning and Text model","authors":"E. Phaisangittisagul, Y. Koobkrabee, K. Wirojborisuth, T. Ratanasrimetha, S. Aummaro","doi":"10.1109/ICTEMSYS.2019.8695956","DOIUrl":null,"url":null,"abstract":"In recent years, there has been a great interest in online advertising not only to promote products and services but to build a brand of the company as well. To satisfy customer needs, some businesses apply intelligent technology to advertise their products and services based on customer interests. Other advertisers allow customers or members to upload their promotions using image and/or message to advertise their businesses and services. However, filtering of promotional advertising is an essential part to detect improper information before posting on the websites and social media. As a result, a model to classify promotional advertising is proposed to identify whether relevant promotion content for a specific business or service in order to meet precise customers’ attention. The proposed algorithm in this study based on deep learning is designed to handle promotional image and message in competition with the 2nd KU Data Science Boot Camp 2018. Its performance is evaluated on the promotional advertising data provided by Wongnai. Finally, the accuracy of the proposed method can achieve satisfactory performance of 82.95% in testing data.","PeriodicalId":220516,"journal":{"name":"2019 10th International Conference of Information and Communication Technology for Embedded Systems (IC-ICTES)","volume":"80 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 10th International Conference of Information and Communication Technology for Embedded Systems (IC-ICTES)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICTEMSYS.2019.8695956","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
In recent years, there has been a great interest in online advertising not only to promote products and services but to build a brand of the company as well. To satisfy customer needs, some businesses apply intelligent technology to advertise their products and services based on customer interests. Other advertisers allow customers or members to upload their promotions using image and/or message to advertise their businesses and services. However, filtering of promotional advertising is an essential part to detect improper information before posting on the websites and social media. As a result, a model to classify promotional advertising is proposed to identify whether relevant promotion content for a specific business or service in order to meet precise customers’ attention. The proposed algorithm in this study based on deep learning is designed to handle promotional image and message in competition with the 2nd KU Data Science Boot Camp 2018. Its performance is evaluated on the promotional advertising data provided by Wongnai. Finally, the accuracy of the proposed method can achieve satisfactory performance of 82.95% in testing data.