Year: 2018
Type: conference-paper
Abstract: This paper presents a novel approach to the segmentation of orthographic word forms in contemporary Hebrew, focusing purely on splitting without carrying out morphological analysis or disambiguation.Casting the analysis task as character-wise binary classification and using adjacent character and wordbased lexicon-lookup features, this approach achieves over 98% accuracy on the benchmark SPMRL shared task data for Hebrew, and 97% accuracy on a new out of domain Wikipedia dataset, an improvement of ≈4% and 5% over previous state of the art performance.
DOI: 10.18653/v1/w18-5811
Author: Amir Zeldes
Institution: Georgetown University
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
OpenAlex ID: W2888716945