Semantic relatedness between words is one of the core concepts in natural language
processing, thus making semantic evaluation an important task. In this paper, we present a …

Extracting useful information for sentiment analysis and classification problems from a big
amount of user-generated feedback, such as restaurant reviews, is a crucial task of natural …

Today we see the active development of natural language processing technologies,
including the morphological analysis of word forms. In this context, the development of more …

Machine transliteration, as defined in this paper, is a process of automatically transforming
written script of words from a source alphabet into words of another target alphabet within …

Nowadays, creation of the tagged corpora is becoming one of the most important tasks of
Natural Language Processing (NLP). There are not enough tagged corpora to build …

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 …

The accurate syllabification of words plays a vital role in various Natural Language
Processing applications. Syllabification is a versatile linguistic tool with applications in …

The Turkic family languages are an agglutinative language in that words are derived from
stems (root) by concatenating affixes to it. This property makes a large number of …

There has been an increasing interest in learning cross-lingual word embeddings to transfer
knowledge obtained from a resource-rich language, such as English, to lower-resource …

Stemming is one of the pipeline feature of Information Retrieval and commonly used in
natural language processing and text mining. The main purpose of a stemming process is to …