Word image based latent semantic indexing for conceptual querying in document image databases

Sameek Banerjee, Gaurav Harit, S. Chaudhury
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引用次数: 8

Abstract

In this paper we present an application of latent semantic analysis (LSA) for indexing and retrieval of document images with text. The query is specified as a set of word images and the documents which best match with the query representation in the the latent semantic space are retrieved. We show through extensive experiments on a large database that use of LSA for document images provides improvements in retrieval precision as is the case with electronic text documents.
基于词图像的潜在语义索引在文档图像数据库中的概念查询
本文提出了一种潜在语义分析(LSA)在带文本的文档图像索引和检索中的应用。查询被指定为一组单词图像,并在潜在语义空间中检索与查询表示最匹配的文档。我们通过在一个大型数据库上进行的大量实验表明,对文档图像使用LSA可以提高检索精度,就像电子文本文档的情况一样。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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