Axmedova Xolisa Ilxomovna
@tsuull.uz
Alisher Navoiy nomidagi Toshkent davlat o'zbek tili va adabiyoti univeristeti
RESEARCH, TEACHING, or OTHER INTERESTS
Information Systems, Human-Computer Interaction, Artificial Intelligence, Computer Science
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
Botir Elov, Nilufar Abdurakhmonova, Xolisxon Axmedova, Zilola Xusainova, Aybibi Iskandarova, and Diloram Fattaxova
Springer Nature Singapore
Elov Botir Boltayevich, Abdurahmonova Muqaddas Tursunalievna, Axmedova Xolisxon Ilxomovna, Abdullayeva Oqila Xolmo’minovna, and Kholmukhamedov Bakhtiyor Farkhodovich
Springer Nature Singapore
Sh. S. Sirojiddinov, B. B. Elov, and X. I. Axmedova
EDP Sciences
The problem of automatic processing of natural language remains relevant for more than half a century. One of the important problems in the field of NLP is the creation of a semantic analyzer, which in turn goes through a number of steps. Determining homonymy is important in the semantic analysis of sentences. A method based on rules, a method based on statistical data, and methods based on machine learning are also used to determine homonymy. Statistical methods are mainly used to determine homonymy between grammatically similar word groups. In this article discusses the use of homonymy between two grammatically similar nouns and adjectives using statistical methods, namely Frequency and Bayesian methods. If bigrams and trigrams are used in the Bayesian method, the characteristics of word groups are classified in the frequentist method, and the parameters that can distinguish them are determined. The identified parameters are converted into numbers as a result of observations and probabilistic decisions are made.
Elov Botir Boltayevich, Axmedova Xolisxon Ilxomovna, Primova Mastura Hakim Qizi, and Khudayberganov Nizomaddin Uktambay O'g'li
IEEE
The development of a semantic analyzer of natural language is considered one of the factors that develop the language. Homonymy is one of the main elements of semantic analysis. Different methods can be used for semantic analysis of homonyms. Homonyms can also be determined using Lesk's algorithm. Lesk's algorithm is based on WordNet of natural language. The weight of the compounds of the homonymous word in the sentence entered through WordNet is determined. The meaning of the word homonym was determined according to the compounds with high weight.
Elov Botir Boltayevich, Hamroyeva Shahlo Mirdjonovna, and Axmedova Xolisxon Ilxomovna
Springer Nature Switzerland
Elov Botir Boltayevich and Axmedova Xolisxon Ilxomovna
IEEE
One of the processes of natural language processing is the semantic analysis of texts. An important task of semantic analysis is to distinguish between the meanings of the words in the text and to distinguish their meanings. For the purpose of semantic analysis of homonymous words, they are divided into groups such as homonyms within 2 parts of speechs, homonyms within 3 parts of speechs and homonyms within 4 parts of speechs according to their occurrence within categories. In the Uzbek language, words that form a homonym are divided into 11 groups within 3 parts of speechs. In this article analyzes the linguistic factors that differentiate homonomy words in the Uzbek language, such as adjective or noun or adverb, noun or pronoun or verb, noun or adjective or verb, noun or verb or pronoun, noun or adjective or predicate word, noun or adverb or imitation word, noun or exclamation word or imitation word, noun or adjective or auxiliary, noun or number or verb, noun or verb or imitation word, exclamation word or verb or adverb develops a total of 7 mathematical models.