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Efficient distributed selective search
2016
Information retrieval (Boston)
Simulation and analysis have shown that selective search can reduce the cost of large-scale distributed information retrieval. By partitioning the collection into small topical shards, and then using a resource ranking algorithm to choose a subset of shards to search for each query, fewer postings are evaluated. In this paper we extend the study of selective search into new areas using a fine-grained simulation, examining the difference in efficiency when term-based and sample-based resource
doi:10.1007/s10791-016-9290-6
fatcat:3rl5hm5rivbcbjgjznzkzcff7m