Browsing by Author "Dauylov S."

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    INTRODUCE PREDICTIVE ANALYTICS USING THE NEXT BEST ACTION (NBA) MODELS INTO THE BANKING SYSTEM
    (СДУ хабаршысы - 2020, 2020) Dauylov S. ; Bogdanchikov A.
    Abstract. NBA - is an approach in which each client is initially considered purely individual. It has a close correlation with Predictive analysis. Predictive or prognostic analytics is a set of techniques and methods for analyzing data to build a forecast of future events. The banking system is currently using the method to obtained certain business results from its customers and has increased loyalty, increased income, found new growth points, etc. The classical model of marketing was rather different, it repelled from its existing product line and its parameters. But new models repels from customer’s inclination to purchase a particular product. The aim of this project is to investigate the field of deposit accounts of the banking system by using NBA approach and to show the benefits and possible outcomes. This approach was tested on various aspects of the banking system and showed a number of solutions which can predict the probability of a customer to create a term deposit account.
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    ItemOpen Access
    Introduce predictive analytics using the Next Best Action (NBA) models into the banking system
    (2020) Dauylov S.
    NBA - is an approach in which each client is initially considered purely ‘individual. It has a close correlation with Predictive analysis. Predictive or prognostic analytics is a set of techniques and methods for analyzing data to build a forecast of future events. The banking system is currently using the method to obtained certain business results from its customers and has increased loyalty, increased income, found new growth points, etc. The classical model of marketing was rather different, it repelled from its existing product line and its parameters. But new models repels from customer’s inclination to purchase a particular product. The aim of this project is to investigate the field of deposit accounts of the banking system by using NBA approach and to show the benefits and possible outcomes. This approach was tested on various aspects of the banking system and showed a number of solutions which can predict the probability of a customer to create a term deposit account.
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    ItemOpen Access
    KAZAKH NAMES GENERATOR USING DEEP LEARNING
    (ВЕСТНИК КАЗАХСТАНСКО-БРИТАНСКОГО ТЕХНИЧЕСКОГО УНИВЕРСИТЕТА, №4, 2020) Nurmambetov D.; Dauylov S.; Bogdanchikov A.
    In recent years, sentiment analysis of e-mail messages or social media posts is becoming very popular. It can help people define if they are reading something positive or negative. On the same time, there are some services on the Internet that can help you find or create a new name. When processing the creation, they check the name in other popular languages, so your name does not mean inappropriate things in other languages. For this they bill for 25 thousand US dollars. If there are such services, then there is a demand. In this study, sentiment analysis of e-mails was implemented with using StanfordNLP [1] lemmatizer and classic machine learning algorithms as a classifier. It is applied to real e-mails from Russian speaking mailbox, which means there are both English and Russian messages. Thus, language identification is also added as preprocessing step. In this study only binary sentiment analysis was made, but it can be improved with adding several emotions to be detected. Then another model generates Kazakh names using neural networks, where all Kazakh names data has been collected through various websites. The sentiment analysis model gives 81% accuracy and the joint use of two models allow us to generate new Kazakh names, which are checked with Russian language if they mean something inappropriate. The result can be improved with checking with other languages.