Enhancing the Inside-Outside Recursive Neural Network Reranker for Dependency Parsing

Phong Le

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract / Description of output

We propose solutions to enhance the Inside-Outside Recursive Neural Network (IORNN) reranker of Le and Zuidema (2014). Replacing the original softmax function with a hierarchical softmax using a binary tree constructed by combining output of the Brown clustering algorithm and frequency-based Huffman codes, we significantly reduce the reranker’s computational complexity. In addition, enriching contexts used in the reranker by adding subtrees rooted at (ancestors’) cousin nodes, the accuracy is increased.
Original languageEnglish
Title of host publicationProceedings of the 14th International Conference on Parsing Technologies
Place of PublicationBilbao, Spain
PublisherAssociation for Computational Linguistics
Pages87-91
Number of pages5
DOIs
Publication statusPublished - Jul 2015
Event14th International Conference on Parsing Technologies 2015 - Bilbao, Spain
Duration: 22 Jul 201524 Jul 2015

Conference

Conference14th International Conference on Parsing Technologies 2015
Country/TerritorySpain
CityBilbao
Period22/07/1524/07/15

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