Paper: splitSVM: Fast Space-Efficient non-Heuristic Polynomial Kernel Computation for NLP Applications

ACL ID P08-2060
Title splitSVM: Fast Space-Efficient non-Heuristic Polynomial Kernel Computation for NLP Applications
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2008
Authors

We present a fast, space efficient and non- heuristic 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 sec- ond on modest hardware without loss of accu- racy (a 30 time speedup over existing meth- ods). The method implementation is available as the open-source splitSVM Java library.