多媒体应用:超越相似性搜索

John R. Smith, D. Doermann, Amarnath Gupta, J. Goldstein, U. Shaft, N. Ratha
{"title":"多媒体应用:超越相似性搜索","authors":"John R. Smith, D. Doermann, Amarnath Gupta, J. Goldstein, U. Shaft, N. Ratha","doi":"10.1145/1160939.1160957","DOIUrl":null,"url":null,"abstract":"Relational database systems solve many of the traditional problems for processing of structured data. However, unstructured data in the form of images, video, audio and multimedia is growing at a tremendous rate and introduces new requirements that are not met by today's database engines. One well known example is content-based retrieval that involves similarity searching and indexing in high-dimensional feature spaces. In addition there has been much recent focus on applying machine learning techniques involving semantics modeling, spatio-temporal indexing, multi-modal (audio-, visual-, textual-) integration and relevance feedback searching.","PeriodicalId":346313,"journal":{"name":"Computer Vision meets Databases","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Multimedia applications: beyond similarity searches\",\"authors\":\"John R. Smith, D. Doermann, Amarnath Gupta, J. Goldstein, U. Shaft, N. Ratha\",\"doi\":\"10.1145/1160939.1160957\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Relational database systems solve many of the traditional problems for processing of structured data. However, unstructured data in the form of images, video, audio and multimedia is growing at a tremendous rate and introduces new requirements that are not met by today's database engines. One well known example is content-based retrieval that involves similarity searching and indexing in high-dimensional feature spaces. In addition there has been much recent focus on applying machine learning techniques involving semantics modeling, spatio-temporal indexing, multi-modal (audio-, visual-, textual-) integration and relevance feedback searching.\",\"PeriodicalId\":346313,\"journal\":{\"name\":\"Computer Vision meets Databases\",\"volume\":\"12 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2005-06-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computer Vision meets Databases\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/1160939.1160957\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computer Vision meets Databases","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/1160939.1160957","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

关系数据库系统解决了许多传统的结构化数据处理问题。然而,图像、视频、音频和多媒体等形式的非结构化数据正在以惊人的速度增长,并引入了当今数据库引擎无法满足的新要求。一个众所周知的例子是基于内容的检索,它涉及高维特征空间中的相似性搜索和索引。此外,最近也有很多关注于应用机器学习技术,包括语义建模、时空索引、多模态(音频、视觉、文本)集成和相关反馈搜索。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multimedia applications: beyond similarity searches
Relational database systems solve many of the traditional problems for processing of structured data. However, unstructured data in the form of images, video, audio and multimedia is growing at a tremendous rate and introduces new requirements that are not met by today's database engines. One well known example is content-based retrieval that involves similarity searching and indexing in high-dimensional feature spaces. In addition there has been much recent focus on applying machine learning techniques involving semantics modeling, spatio-temporal indexing, multi-modal (audio-, visual-, textual-) integration and relevance feedback searching.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信