在MARS中支持相似性查询

Michael Ortega-Binderberger, Y. Rui, K. Chakrabarti, S. Mehrotra, Thomas S. Huang
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引用次数: 266

摘要

为了解决需要访问和检索多媒体对象的应用程序的新需求,我们在伊利诺伊大学的团队正在开发多媒体分析和检索系统(MARS)[13]。本文主要研究了MARS的检索子系统及其对图像数据库基于内容查询的支持。基于内容的文本检索技术在自动信息检索领域得到了广泛的研究[24,21]。本文描述了如何将这些技术用于图像数据库上的排名重试。具体来说,我们讨论了基于布尔检索模型在MARS中开发的排序和检索算法,并描述了我们的实验结果,证明了所开发模型在图像检索中的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Supporting similarity queries in MARS
To address the emerging needs of applications that require access to and retrieval of multimedia objects, we are developing the Multimedia Analysis and Retrieval System (MARS) in our group at the University of Illinois [13]. In this paper, we concentrate on the retrieval subsystem of MARS and its support for content-based queries over image databases. Content-based retrieval techniques have been extensively studied for textual documents in the area of automatic information retrieval [24, 21. This paper describes how these techniques can be adapted for ranked retried over image databases. Specifically, we discuss the ranking and retrieval algorithms developed in MARS based on the Boolean retrievaI model and describe the results of our experiments that demonstrate the effectiveness of the developed model for image retrieval.
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