A Graph Auto-encoder Model of Derivational Morphology
2020pp. 1127–1138
Citations Over TimeTop 17% of 2020 papers
Abstract
There has been little work on modeling the morphological well-formedness (MWF) of derivatives, a problem judged to be complex and difficult in linguistics We present a graph auto-encoder that learns embeddings capturing information about the compatibility of affixes and stems in derivation. The auto-encoder models MWF in English surprisingly well by combining syntactic and semantic information with associative information from the mental lexicon.
Related Papers
- → Automatic Construction of a Core Lexicon for Specific Domain(2007)6 cited
- VARIAN LEKSIKON BAHASA JAWA PADA WILAYAH SEGITIGA DI KABUPATEN WONOSOBO(2017)
- An Analysis of Combining and Pragmatic Motivations on "Internet Fashionable Lexicon(2003)
- → The Use of Terminological Lexicon in Making Phraseological Units(2017)
- → existence of lexicon Taru Pramana on Balinese traditional medicine(2021)