We explore different techniques for pruning an inverted index in advance, that is, without building the full index. These techniques provide interesting trade-offs between index size, answer quality and query coverage. We experimentally analyze them in a large public web collection with two different query logs. The trade-offs that we find range from an index of size 4% and 35% of precision@10 to an index of size 46% and 90% of precision@10, with respect to the full index case. In both cases we cover ...
We explore different techniques for pruning an inverted index in advance, that is, without building the full index. These techniques provide interesting trade-offs between index size, answer quality and query coverage. We experimentally analyze them in a large public web collection with two different query logs. The trade-offs that we find range from an index of size 4% and 35% of precision@10 to an index of size 46% and 90% of precision@10, with respect to the full index case. In both cases we cover almost 97% of the query volume. We also do a relative relevance analysis with a smaller private web collection and query log, finding that some of our techniques allow a reduction of almost 40% the index size by losing less than 2% for NDCG@10.
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