Robust Selective Search

ACM SIGIR Forum(2019)

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摘要
Selective search is a modern distributed search architecture designed to reduce the computational cost of large-scale search. Selective search creates topical shards that are deliberately content-skewed, placing highly similar documents together in the same shard. During query time, rather than searching the entire corpus, a resource selection algorithm selects a subset of the topic shards likely to contain documents relevant to the query and search is only performed on these shards. This substantially reduces total computational costs of search while maintaining accuracy comparable to exhaustive distributed search.
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