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An n-gram cache for large-scale parallel extraction of multiword relevant expressions with LocalMaxs

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LocalMaxs extracts relevant multiword terms based on their cohesion but is computationally intensive, a critical issue for very large natural language corpora. The corpus properties concerning n-gram distribution determine the algorithm complexity and were empirically analyzed for corpora up to 982 million words. A parallel LocalMaxs implementation exhibits almost linear relative efficiency, speedup, and sizeup, when executed with up to 48 cloud virtual machines and a distributed key-value store. To reduce the remote data communication, we present a novel n-gram cache with cooperative-based warm-up, leading to reduced miss ratio and time penalty. A cache analytical model is used to estimate the performance of cohesion calculation of n-gram expressions, based on corpus empirical data. The model estimates agree with the real execution results.

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Large corpora Statistical extraction Multiword terms Parallel processing n-gram cache Performance evaluation Cloud computing

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GONÇALVES, Carlos; SILVA, Joaquim F.; CUNHA, José C. – An n-gram cache for large-scale parallel extraction of multiword relevant expressions with LocalMaxs. In Proceeding of the 2016 IEEE 12th International Conference on e-Science (e-Science). Baltimore, MD, USA: IEEE, 2016. ISBN 978-1-5090-4273-9. Pp. 120-129

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Institute of Electrical and Electronics Engineers

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