Abstract

AbstractWe describe the implementation of a data compression scheme as an integral and transparent layer within a full‐text retrieval system. Using a semi‐static word‐based compression model, the space needed to store the text is under 30 per cent of the original requirement. The model is used in conjunction with canonical Huffman coding and together these two paradigms provide fast decompression. Experiments with 500 Mb of newspaper articles show that in full‐text retrieval environments compression not only saves space, it can also yield faster query processing ‐ a win‐win situation.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.