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- W2006997130 abstract "We introduce static index pruning methods that significantly reduce the index size in information retrieval systems.We investigate uniform and term-based methods that each remove selected entries from the index and yet have only a minor effect on retrieval results. In uniform pruning, there is a fixed cutoff threshold, and all index entries whose contribution to relevance scores is bounded above by a given threshold are removed from the index. In term-based pruning, the cutoff threshold is determined for each term, and thus may vary from term to term. We give experimental evidence that for each level of compression, term-based pruning outperforms uniform pruning, under various measures of precision. We present theoretical and experimental evidence that under our term-based pruning scheme, it is possible to prune the index greatly and still get retrieval results that are almost as good as those based on the full index." @default.
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- W2006997130 date "2001-09-01" @default.
- W2006997130 modified "2023-10-04" @default.
- W2006997130 title "Static index pruning for information retrieval systems" @default.
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- W2006997130 doi "https://doi.org/10.1145/383952.383958" @default.
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