Unsupervised Affix Identification Approach using Probabilistic Dependence

Autor:	Abeer Alsheddi, Ahmed Khorsi
Rok vydání:	2018
Předmět:	Root (linguistics) Arabic Computer science business.industry Affix Probabilistic logic computer.software_genre language.human_language Identification (information) language Artificial intelligence Computational linguistics business computer Word (computer architecture) Natural language processing
Zdroj:	2018 1st International Conference on Computer Applications & Information Security (ICCAIS).
DOI:	10.1109/cais.2018.8441938
Popis:	It is difficult to identify an affix letter from a root letter in a given word in many NLP applications. This challenge is even harder in morphologically complex languages, such as Arabic. This paper investigates to identify affix letters using probabilistic dependence concept with an unsupervised method. A relationship is shown when 90% of the negative dependence points appeared at the affix letters.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::504c1de2515d7181685e00d40347814f https://doi.org/10.1109/cais.2018.8441938 Zobrazit plný text záznamu