Year: 2015
Type: article
Abstract: This paper describes a semi-supervised approach to improving statistical dependency parsing using dependency-based word clusters.After applying a baseline parser to unlabeled text, clusters are induced using K-means with word features based on the dependency structures.The parser is then re-trained using information about the clusters, yielding improved parsing accuracy on a range of different data sets, including WSJ and the English Web Treebank.We report improved results using both in-domain and out-of-domain data, and also include a comparison with using n-gram-based Brown clustering.
Authors: Jostein Lien, Erik Velldal, Lilja Øvrelid
Institution: University of Oslo
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2128976668