SIGIR '92 Proceedings of the 15th annual international ACM SIGIR conference on Research and development in information retrieval
Exploring the similarity space
ACM SIGIR Forum
Shortest-substring retrieval and ranking
ACM Transactions on Information Systems (TOIS)
A probabilistic model of information retrieval: development and comparative experiments
Information Processing and Management: an International Journal
Internet Document Filtering Using Fourier Domain Scoring
PKDD '01 Proceedings of the 5th European Conference on Principles of Data Mining and Knowledge Discovery
A Novel Web Text Mining Method Using the Discrete Cosine Transform
PKDD '02 Proceedings of the 6th European Conference on Principles of Data Mining and Knowledge Discovery
A new implementation technique for fast Spectral based document retrieval systems
ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
Fourier Domain Scoring: A Novel Document Ranking Method
IEEE Transactions on Knowledge and Data Engineering
A Novel Document Ranking Method Using the Discrete Cosine Transform
IEEE Transactions on Pattern Analysis and Machine Intelligence
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The fast vector space and probabilistic methods use the term counts and the slower proximity methods use term positions. We present the spectral-based information retrieval method which is able to use both term count and position information to obtain high precision document rankings. We are able to perform this, in a time comparable to the vector space method, by examining the query term spectra rather than query term positions. This method is a generalisation of the vector space method (VSM). Therefore, our spectral method can use the weighting schemes and enhancements used in the VSM.