Fourier domain scoring: A novel document ranking method

  • Park L
  • Ramamohanarao K
  • Palaniswami M
  • 10


    Mendeley users who have this article in their library.
  • 27


    Citations of this article.


Current document retrieval methods use a vector space similarity measure to give scores of relevance to documents when related to a specific query. The central problem with these methods is that they neglect any spatial information within the documents in question. We present a new method, called Fourier Domain Scoring (FDS), which takes advantage of this spatial information, via the Fourier transform, to give a more accurate ordering of relevance to a document set. We show that FDS gives an improvement in precision over the vector space similarity measures for the common case of Web like queries, and it gives similar results to the vector space measures for longer queries.

Author-supplied keywords

  • Document ranking
  • Fourier domain scoring
  • Fourier transform
  • Information retrieval
  • Search engine
  • Term signal
  • Vector space similarity measure

Get free article suggestions today

Mendeley saves you time finding and organizing research

Sign up here
Already have an account ?Sign in

Find this document


  • Laurence A.F. Park

  • Kotagiri Ramamohanarao

  • Marimuthu Palaniswami

Cite this document

Choose a citation style from the tabs below

Save time finding and organizing research with Mendeley

Sign up for free