相关论文: Stemmer for Serbian language
In this paper, a novel hierarchical Persian stemming approach based on the Part-Of-Speech of the word in a sentence is presented. The implemented stemmer includes hash tables and several deterministic finite automata in its different levels…
This paper presents a method of stemming for the Arabian texts based on the linguistic techniques of the natural language processing. This method leans on the notion of scheme (one of the strong points of the morphology of the Arabian…
We live in a translingual society, in order to communicate with people from different parts of the world we need to have an expertise in their respective languages. Learning all these languages is not at all possible; therefore we need a…
This paper provides a method for indexing and retrieving Arabic texts, based on natural language processing. Our approach exploits the notion of template in word stemming and replaces the words by their stems. This technique has proven to…
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 and grammatical…
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.…
Automated terminology extraction refers to the task of extracting meaningful terms from domain-specific texts. This paper proposes a novel machine learning approach to terminology extraction, which combines features from traditional term…
Morphological analysis and disambiguation is an important task and a crucial preprocessing step in natural language processing of morphologically rich languages. Kinyarwanda, a morphologically rich language, currently lacks tools for…
Inflection is an essential part of every human language's morphology, yet little effort has been made to unify linguistic theory and computational methods in recent years. Methods of string manipulation are used to infer inflectional…
Lemmatization is a natural language processing (NLP) task which consists of producing, from a given inflected word, its canonical form or lemma. Lemmatization is one of the basic tasks that facilitate downstream NLP applications, and is of…
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. The main purpose…
We present an experiment in extracting adjectives which express a specific semantic relation using word embeddings. The results of the experiment are then thoroughly analysed and categorised into groups of adjectives exhibiting formal or…
We propose new static word embeddings optimised for sentence semantic representation. We first extract word embeddings from a pre-trained Sentence Transformer, and improve them with sentence-level principal component analysis, followed by…
Compounding is a highly productive word-formation process in some languages that is often problematic for natural language processing applications. In this paper, we investigate whether distributional semantics in the form of word…
Neural language models (LMs) have shown to benefit significantly from enhancing word vectors with subword-level information, especially for morphologically rich languages. This has been mainly tackled by providing subword-level information…
Language models (LMs) automatically learn word embeddings during pre-training on language corpora. Although word embeddings are usually interpreted as feature vectors for individual words, their roles in language model generation remain…
Matching texts in highly inflected languages such as Arabic by simple stemming strategy is unlikely to perform well. In this paper, we present a strategy for automatic text matching technique for for inflectional languages, using Arabic as…
In this paper we present a fundamental lexical semantics of Sinhala language and a Hidden Markov Model (HMM) based Part of Speech (POS) Tagger for Sinhala language. In any Natural Language processing task, Part of Speech is a very vital…
Self-adjusting computation offers a language-based approach to writing programs that automatically respond to dynamically changing data. Recent work made significant progress in developing sound semantics and associated implementations of…
Placeholder translation systems enable the users to specify how a specific phrase is translated in the output sentence. The system is trained to output special placeholder tokens, and the user-specified term is injected into the output…