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Optimizing Dependency Parsing Throughput

Weichselbraun, Albert and Süsstrunk, Norman (2015) Optimizing Dependency Parsing Throughput. In: Proceedings of the 7th International Conference on Knowledge Discovery and Information Retrieval (KDIR 2015), 12-14 November 2015, Lisbon, Portugal. (In Press)

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Dependency parsing is considered a key technology for improving information extraction tasks. Research indicates that dependency parsers spend more than 95 of their total runtime on feature computations. Based on this insight, this paper investigates the potential of improving parsing throughput by designing feature representations which are optimized for combining single features to more complex feature templates and by optimizing parser constraints. Applying these techniques to MDParser increased its throughput four fold, yielding Syntactic Parser, a dependency parser that outperforms comparable approaches by factor 25 to 400.

Item Type:Conference or Workshop Item (Paper)
Additional Information:Accepted 21 September 2015
Uncontrolled Keywords:natural language processing, dependency parsing, performance optimization, throughput
Subjects:Q Science > QA Mathematics > QA76 Computer software
Divisions:Faculty of Engineering, Science and Mathematics > School of Electronics and Computer Science
ID Code:86
Deposited By: Dr Albert Weichselbraun
Deposited On:22 Oct 2015 08:05
Last Modified:22 Oct 2015 08:05

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