Uzbek affix finite state machine for stemming
This work presents a morphological analyzer for the Uzbek language using a finite state machine. The proposed methodology is a morphologic analysis of Uzbek words by using an affix striping to find a root and without including any lexicon. This method helps to perform morphological analysis of words from a large amount of text at high speed as well as it is not required using of memory for keeping vocabulary. According to Uzbek, an agglutinative language can be designed with finite state machines (FSMs). In contrast to the previous works, this study modeled the completed FSMs for all word classes by using the Uzbek language's morphotactic rules in right to left order. This paper shows the stages of this methodology including the classification of the affixes, the generation of the FSMs for each affix class, and the combination into a head machine to make analysis a word.
Code (0)
등록된 구현이 없습니다.
Tasks
Morphological AnalysisMethods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
UzbekStemmer: Development of a Rule-Based Stemming Algorithm for Uzbek Language
In this paper we present a rule-based stemming algorithm for the Uzbek language. Uzbek is an agglutinative language, so many words are formed by adding suffixes, and the number of suffixes is also large. For this reason,…
Development of a rule-based lemmatization algorithm through Finite State Machine for Uzbek language
Lemmatization is one of the core concepts in natural language processing, thus creating a lemmatization tool is an important task. This paper discusses the construction of a lemmatization algorithm for the Uzbek language…
LEMMALemmatizationUzMorphAnalyser: A Morphological Analysis Model for the Uzbek Language Using Inflectional Endings
As Uzbek language is agglutinative, has many morphological features which words formed by combining root and affixes. Affixes play an important role in the morphological analysis of words, by adding additional meanings a…
Morphological AnalysisUzbekTagger: The rule-based POS tagger for Uzbek language
This research paper presents a part-of-speech (POS) annotated dataset and tagger tool for the low-resource Uzbek language. The dataset includes 12 tags, which were used to develop a rule-based POS-tagger tool. The corpus…
Language ModelingLanguage ModellingMachine TranslationPOS+6BBPOS: BERT-based Part-of-Speech Tagging for Uzbek
This paper advances NLP research for the low-resource Uzbek language by evaluating two previously untested monolingual Uzbek BERT models on the part-of-speech (POS) tagging task and introducing the first publicly availab…
Part-Of-Speech TaggingPOSPOS TaggingSensitivity