Graph-based lemmatization of Turkish words by using morphological similarity

Arslan, Enıs; Orhan, Umut

doi:10.1109/inista.2016.7571835

Cited by 4 publications

(3 citation statements)

References 14 publications

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“…NLP is relied on tokenization of text documents and processing the matrix related to tokens. Typical tokenization techniques include affix removal, successor variety, table lookup, N-gram [2], LemmaGen [3], Dictionary Based Search by Removing Affix (DBSRA) [4], and Graph-based lemmatization [5]. Different languages require different tokenization techniques.…”

Section: Artificial Intelligence (Ai)mentioning

confidence: 99%

Smart augmented reality with AI service expert for world's industries

Madeleine¹,

Martinsen²,

Zhou³

et al. 2022

Preprint

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Section: Artificial Intelligence (Ai)mentioning

confidence: 99%

Smart augmented reality with AI service expert for world's industries

Madeleine¹,

Martinsen²,

Zhou³

et al. 2022

Preprint

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show abstract

“…There are lots of studies related with morphological structure of Turkish [31], [32]. Suffixes are also used to transform basic word types (noun, adjective and verb).…”

Section: Transformation Structure With Suffixesmentioning

confidence: 99%

“…Turkish is a agglutinative language so suffixes are deterministic features for phrase types; subject type; singularity or plurality; time and model type. There are lots of studies related with morphological structure of Turkish [31], [32]. Suffixes are also used to transform basic word types (noun, adjective and verb).…”

Section: Transformation Structure With Suffixesmentioning

confidence: 99%

Contex Free Grammer For Turkish

Dönmez

Adalı

2018

SDÜ Fen Bil Enst Der

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Formal Grammar which is introduced by Chomsky is one of the most important development in Natural Language Processing, a branch of Artificial Intelligence. The mathematical reresentation of languages can be possible using Formal Grammars. Almost all natural languages have word classes such as noun, adjective, verb. In addition to this one sentence consist of noun phrase and verb phrase. Noun phrase may consist of location, destination and source elements. Despite many similarities between the languages, there exist important dissimilarities in grammar rules of the languages belonging to different language families. In our study the most appropriate formal grammar representing Turkish language is investigated. Accuracy of the suggested grammars' rules is evaluated in two different corpus. This study is the enhanced version of "Turkish Context Free Grammar Rules with Case Suffix and Phrase Relation" that was presented on UBMK 2016 International Conference on Computer Science & Engineering [1]. Different from the first study, this study includes all word and sentence types of Turkish. Adjectives and prepositions are considered. The quoted sentences, incomplete sentences and question sentences are included. The genitive phrase structures including verbal word are included. In this study, the noun phrases are also defined in detail.

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