Abstract
Current information retrieval methods either ignore the term positions or deal with exact term positions; the former can be seen as coarse document resolution, the latter as fine document resolution. We propose a new spectral-based information retrieval method that is able to utilize many different levels of document resolution by examining the term patterns that occur in the documents. To do this, we take advantage of the multiresolution analysis properties of the wavelet transform. We show that we are able to achieve higher precision when compared to vector space and proximity retrieval methods, while producing fast query times and using a compact index.
| Original language | English |
|---|---|
| Pages (from-to) | 267-298 |
| Number of pages | 32 |
| Journal | ACM Transactions on Information Systems |
| Volume | 23 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - Jul 2005 |
| Externally published | Yes |
Keywords
- Daubechies
- Document retrieval
- Haar
- Multiresolution analysis
- Proximity search
- Vector space methods
- Wavelet transform
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