Premium
Resource‐Light Approaches to Computational Morphology Part 1: Monolingual Approaches
Author(s) -
Hana Jirka,
Feldman Anna
Publication year - 2012
Publication title -
language and linguistics compass
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.619
H-Index - 44
ISSN - 1749-818X
DOI - 10.1002/lnc3.358
Subject(s) - software portability , granularity , computer science , resource (disambiguation) , artificial intelligence , natural language processing , data science , machine learning , programming language , computer network
This article surveys resource‐light monolingual approaches to morphological analysis and tagging. While supervised analyzers and taggers are very accurate, they are extremely expensive to create. Therefore, most of the world languages and dialects have no realistic prospect for morphological tools created in this way. The weakly‐supervised approaches aim to minimize time, expertise and/or financial cost needed for their development. We discuss the algorithms and their performance considering issues such as accuracy, portability, development time and granularity of the output.