A new implementation technique for fast spectral based document retrieval systems

The traditional methods of spectral text retrieval (FDS,CDS) create an index of spatial data and convert the data to its spectral form at query time. We present a new method of implementing and querying an index containing spectral data which will conserve the high precision performance of the spectral methods, reduce the time needed to resolve the query, and maintain an acceptable size for the index. This is done by taking advantage of the properties of the discrete cosine transform and by applying ideas from vector space document ranking methods.