{"title":"从图像内容的自由文本描述中提取主题相关关键字进行标记","authors":"Joonmyun Cho, Yoon-Seop Chang, Sung-Ho Lee","doi":"10.23919/ICACT.2018.8323821","DOIUrl":null,"url":null,"abstract":"This paper discusses a method for automatic theme-related keyword extraction from users' natural language comments on their photographs and videos. ‘Theme’ indicates the concepts circumscribing and describing the content of the photos and videos such as pets, natural sites, palaces and places. The method employs a deep learning algorithm, RNN(Recurrent Neural Network) that is good at recognizing implicit patterns of sequential data. The method has been applied to the construction of a place-related image content DB, and delivers reasonably good performance even in case the measure (i.e. themes of image contents) is abstract and vague.","PeriodicalId":228625,"journal":{"name":"2018 20th International Conference on Advanced Communication Technology (ICACT)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Theme-related keyword extraction from free text descriptions of image contents for tagging\",\"authors\":\"Joonmyun Cho, Yoon-Seop Chang, Sung-Ho Lee\",\"doi\":\"10.23919/ICACT.2018.8323821\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper discusses a method for automatic theme-related keyword extraction from users' natural language comments on their photographs and videos. ‘Theme’ indicates the concepts circumscribing and describing the content of the photos and videos such as pets, natural sites, palaces and places. The method employs a deep learning algorithm, RNN(Recurrent Neural Network) that is good at recognizing implicit patterns of sequential data. The method has been applied to the construction of a place-related image content DB, and delivers reasonably good performance even in case the measure (i.e. themes of image contents) is abstract and vague.\",\"PeriodicalId\":228625,\"journal\":{\"name\":\"2018 20th International Conference on Advanced Communication Technology (ICACT)\",\"volume\":\"39 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 20th International Conference on Advanced Communication Technology (ICACT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.23919/ICACT.2018.8323821\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 20th International Conference on Advanced Communication Technology (ICACT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/ICACT.2018.8323821","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Theme-related keyword extraction from free text descriptions of image contents for tagging
This paper discusses a method for automatic theme-related keyword extraction from users' natural language comments on their photographs and videos. ‘Theme’ indicates the concepts circumscribing and describing the content of the photos and videos such as pets, natural sites, palaces and places. The method employs a deep learning algorithm, RNN(Recurrent Neural Network) that is good at recognizing implicit patterns of sequential data. The method has been applied to the construction of a place-related image content DB, and delivers reasonably good performance even in case the measure (i.e. themes of image contents) is abstract and vague.