Performance evaluation of DCT and wavelet transform for LSI

Latent semantic indexing (LSI) is commonly used to match queries to documents in information retrieval (IR) applications. This paper presents a new philosophy for LSI, investigating the use of various hybrid approaches and presents a novel evaluation strategy based on the use of image processing tools. The authors evaluate the use of the discrete cosine transform (DCT) and Cohen Daubechies Feauveau 9/7 (CDF9/7) wavelet transform as a pre-processing step for the singular value decomposition (SVD) step of the LSI system. In addition, the effect of different threshold types on the search results is examined. The results show that accuracy can be increased by applying both transforms as a pre-processing step, with better performance for the hard-threshold function. The choice of the best threshold value is a key factor in the transform process.