Кафедра "Інтелектуальні комп'ютерні системи"

Постійне посилання колекціїhttps://repository.kpi.kharkov.ua/handle/KhPI-Press/2423

Офіційний сайт кафедри http://web.kpi.kharkov.ua/iks

Кафедра "Інтелектуальні комп’ютерні системи" заснована 12 лютого 2007 року на базі спеціальності "Прикладна лінгвістика".

У 2009 році на базі кафедри спільно з Українським мовно-інформаційним фондом НАН України було створено Науково-дослідний центр інтелектуальних систем і комп’ютерної лінгвістики.

Кафедра входить до складу Навчально-наукового інституту соціально-гуманітарних технологій Національного технічного університету "Харківський політехнічний інститут".

У складі науково-педагогічного колективу кафедри працюють: 2 доктора технічних наук, 5 кандидатів філологічних наук, 4 кандидата технічних наук, 1 кандидат філософських наук; 2 співробітника мають звання професора, 3 – доцента.

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Фільтри

2014 - 20163

Налаштування

Автор: search.filters.author.Gautam, Ajit Pratap Singh

Результати пошуку

Зараз показуємо 1 - 3 з 3
  • Ескіз
    Документ
    The Logical-Linguistic Model of Fact Extraction from English Texts
    (2016) Khairova, N. F.; Petrasova, S. V.; Gautam, Ajit Pratap Singh
    In this paper we suggest the logical-linguistic model that allows extracting required facts from English sentences. We consider the fact in the form of a triplet: Subject > Predicate > Object with the Predicate representing relations and the Object and Subject pointing out two entities. The logical-linguistic model is based on the use of the grammatical and semantic features of words in English sentences. Basic mathematical characteristic of our model is logical-algebraic equations of the finite predicates algebra. The model was successfully implemented in the system that extracts and identifies some facts from Web-content of a semi-structured and non-structured English text.
  • Ескіз
    Документ
    A Survey of Association Rule Mining for Customer Relationship Management
    (2014) Gautam, Ajit Pratap Singh; Sharonova, Natalia Valeriyevna
    Data mining technique is most frequently used in Customer Relationship Management field. There are many data mining algorithm and methods can be used in solving CRM problems. Association Rule Mining technique is widely used in CRM application. Various algorithms has been proposed by various researches. This paper is an effort to analyze these algorithms in view of their implementation in Customer Relationship Management.
  • Ескіз
    Документ
    The logic and linguistic model for automatic extraction of collocation similarity
    (University of Engineering and Economics, Poland, 2015) Khairova, N. F.; Petrasova, S. V.; Gautam, Ajit Pratap Singh
    The article discusses the process of automatic identification of collocation similarity. The semantic analysis is one of the most advanced as well as the most difficult NLP task. The main problem of semantic processing is the determination of polysemy and synonymy of linguistic units. In addition, the task becomes complicated in case of word collocations. The paper suggests a logical and linguistic model for automatic determining semantic similarity between colocations in Ukraine and English languages. The proposed model formalizes semantic equivalence of collocations by means of semantic and grammatical characteristics of collocates. The basic idea of this approach is that morphological, syntactic and semantic characteristics of lexical units are to be taken into account for the identification of collocation similarity. Basic mathematical means of our model are logical-algebraic equations of the finite predicates algebra. Verb-noun and noun-adjective collocations in Ukrainian and English languages consist of words belonged to main parts of speech. These collocations are examined in the model. The model allows extracting semantically equivalent collocations from semi-structured and non-structured texts. Implementations of the model will allow to automatically recognize semantically equivalent collocations. Usage of the model allows increasing the effectiveness of natural language processing tasks such as information extraction, ontology generation, sentiment analysis and some others.