{"title":"A Metadata Extraction Method for Taste-Impression with Sensor Technologies","authors":"Hanako Kariya, Y. Kiyoki","doi":"10.1109/SAINTW.2005.13","DOIUrl":null,"url":null,"abstract":"In this paper, we present a metadata extraction method for taste-impression with sensor technologies. Our metadata extraction method extracts taste-impression metadata automatically by using sensor outputs retrieved from the taste sensor, according to characteristic features of foods, such as a type, a nationality, and a theme (\"taste domain\"). By realizing taste-domain-dependent metadata extraction with sensor technologies, our method transforms sensor outputs into meaningful taste-impression metadata automatically and computes the correlation between the target foods (or drinks) and the query described in tasteimpression. Users can intuitively search various information resources regarding foods and drinks on the basis of abstract taste-impression preferences. We clarify the feasibility and effectiveness of our method by several experimental results.","PeriodicalId":220913,"journal":{"name":"2005 Symposium on Applications and the Internet Workshops (SAINT 2005 Workshops)","volume":"281 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2005 Symposium on Applications and the Internet Workshops (SAINT 2005 Workshops)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SAINTW.2005.13","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
In this paper, we present a metadata extraction method for taste-impression with sensor technologies. Our metadata extraction method extracts taste-impression metadata automatically by using sensor outputs retrieved from the taste sensor, according to characteristic features of foods, such as a type, a nationality, and a theme ("taste domain"). By realizing taste-domain-dependent metadata extraction with sensor technologies, our method transforms sensor outputs into meaningful taste-impression metadata automatically and computes the correlation between the target foods (or drinks) and the query described in tasteimpression. Users can intuitively search various information resources regarding foods and drinks on the basis of abstract taste-impression preferences. We clarify the feasibility and effectiveness of our method by several experimental results.