Aspect-oriented definition of emotional tonality of documents in the Kazakh language.
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Date
2018
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Abstract
In our time, every person in his everyday life is facing artificial intelligence even without noticing it. We use it literally everywhere, from searching the Internet and ending with the location of a fast route from point A to point B. Over the past 10 years, developments in the field of artificial intelligence have acquired a new breath. Since many studies were made as far back as the twentieth century, they were not used in the right case because there was a lack of a large amount of data. But now in the world there is a lot of data on which it is possible to train and create the so-called weak artificial intelligence (weak AI) which performs one specific task. A good example of a weak AI is Apple Siri and Google Assistant. The task of which is to Support the conversation with a real person (Question & Answering). Along with this, in the processing of natural language there are other tasks such as the sentiment analysis of the text, machine translation and speech recognition. The sentiment analysis of the text is used in many ways to understand the end user, but applications for analyzing the mood are endless. More and more we see that it is used in monitoring social networks and VOC (voice of the customer) to track Customer feedback, survey responses, competitors, etc. However, it is also practical for use in business analytics and situations, in which the text needs analysis. In such areas as product quality development, improvement of customer service, and crisis Management. In this thesis, the work of the application, which will determine the emotional tone of the text in the Kazakh language, will be explained. As the input, we will give the text in Kazakh. and the program should accordingly give an answer in the form of Negative or positive.
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person, artificial intelligence, Apple Siri, Google Assistant