Text retrieval using sparsified concept decomposition matrix

3Citations
Citations of this article
8Readers
Mendeley users who have this article in their library.
Get full text

Abstract

We examine text retrieval strategies using the sparsified concept decomposition matrix. The centroid vector of a tightly structured text collection provides a general description of text documents in that collection. The union of the centroid vectors forms a concept matrix. The original text data matrix can be projected into the concept space spanned by the concept vectors. We propose a procedure to conduct text retrieval based on the sparsified concept decomposition (SCD) matrix. Our experimental results show that text retrieval based on SCD may enhance the retrieval accuracy and reduce the storage cost, compared with the popular text retrieval technique based on latent semantic indexing with singular value decomposition. © Springer-Verlag 2004.

Cite

CITATION STYLE

APA

Gao, J., & Zhang, J. (2004). Text retrieval using sparsified concept decomposition matrix. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 3314, 523–529. https://doi.org/10.1007/978-3-540-30497-5_82

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free