splitSVM: Fast, Space-efficient, non-Heuristic, polynomial kernel computation for NLP applications

Yoav Goldberg, Michael Elhadad

Research output: Contribution to journalArticlepeer-review

69 Scopus citations

Abstract

We present a fast, space efficient and nonheuristic method for calculating the decision function of polynomial kernel classifiers for NLP applications. We apply the method to the MaltParser system, resulting in a Java parser that parses over 50 sentences per second on modest hardware without loss of accuracy (a 30 time speedup over existing methods). The method implementation is available as the open-source splitSVM Java library. © 2012, American College of Rheumatology.

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