Latent Semantic Indexing using Multiresolution Analysis

Latent semantic indexing (LSI) is commonly used to match queries to documents in information retrieval (IR) applications. It has been shown to improve the retrieval performance, as it can deal with synonymy and polysemy problems. This paper proposes a hybrid approach which can improve result accuracy significantly. Evaluation of the approach based on using the Haar wavelet transform (HWT) as a preprocessing step for the singular value decomposition (SVD) in the LSI system is presented, using Donoho′s thresholding with the transformation in HWT. Furthermore, the effect of different levels of decomposition in the HWT process is investigated. The experimental results presented in the paper confirm a significant improvement in performance by applying the HWT as a preprocessing step using Donoho′s thresholding.