• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Information Processing & Management >A relational vector space model using an advanced weighting scheme for image retrieval
【24h】

A relational vector space model using an advanced weighting scheme for image retrieval

机译：使用高级加权方案进行图像检索的关系向量空间模型

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

In this paper, we lay out a relational approach for indexing and retrieving photographs from a collection. The increase of digital image acquisition devices, combined with the growth of the World Wide Web, requires the development of information retrieval (IR) models and systems that provide fast access to images searched by users in databases. The aim of our work is to develop an IR model suited to images, integrating rich semantics for representing this visual data and user queries, which can also be applied to large corpora. Our proposal merges the vector space model of IR - widely tested in textual IR - with the conceptual graph (CG) formalism, based on the use of star graphs (i.e. elementary CGs made up of a single relation connected to some concepts representing image objects). A novel weighting scheme for star graphs, based on image objects size, position, and image heterogeneity is outlined. We show that integrating relations into the vector space model through star graphs increases the system's precision, and that the results are comparable to those from graph projection systems, and also that they shorten processing time for user queries.
机译：在本文中，我们提出了一种从索引中检索和检索照片的关系方法。数字图像采集设备的增加，以及万维网的增长，要求开发信息检索（IR）模型和系统，以提供对用户在数据库中搜索的图像的快速访问。我们的工作目标是开发一种适用于图像的IR模型，集成用于表示此可视数据和用户查询的丰富语义，该模型也可以应用于大型语料库。我们的建议将基于文本IR的IR矢量空间模型（在文本IR中经过广泛测试）与概念图（CG）形式主义相结合，基于星形图的使用（即基本CG由与表示图像对象的某些概念相连的单个关系组成） 。概述了一种基于图像对象大小，位置和图像异质性的星形图加权方法。我们表明，通过星图将关系集成到向量空间模型中可以提高系统的精度，其结果与图投影系统的结果相当，并且可以缩短用户查询的处理时间。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号