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In this paper, the authors present the first scalable parallel solution for the All Pairs Similarity Search (APSS) problem, which involves finding all pairs of data records that have a similarity score above the specified threshold. With exponentially growing datasets and modern multi-processor/multi-core system architectures, serial nature of all existing APSS solutions is the major rate limiting factor for applicability of APSS to large-scale real-world problems and calls for parallelization. Their proposed index sharing technique divides the APSS computation into independent searches over the central inverted index shared across all processors as a read-only data structure and achieves linear speed-up over the fastest serial APSS algorithm in shared memory environment.
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