TDM modeling and evaluation of different domain transforms for LSI

Authors:
Tareq Jaber;Abbes Amira;Peter Milligan
Affiliations:
School of Electronics, Electrical Engineering and Computer Science, Queen's University Belfast, Belfast BT7 1NN, UK;Electronic and Computer Engineering, School of Engineering and Design, Brunel University, West London, Uxbridge, Middlesex UB8 3PH, UK;School of Electronics, Electrical Engineering and Computer Science, Queen's University Belfast, Belfast BT7 1NN, UK
Venue:
Neurocomputing
Year:
2009

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Abstract

Latent semantic indexing (LSI) is a popular technique used in information retrieval (IR) applications. This paper 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 preprocessing 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 preprocessing step, with better performance for the hard-threshold function. The choice of the best threshold value is a key factor in the transform process. This paper also describes the most effective structure for the database to facilitate efficient searching in the LSI system.