Development of Recommendation System for Online Library
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Date
2023
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Abstract
This dissertation is devoted to the development of a recommendation system for an online library. The aim of the research is to create an efficient and personalized recommendation system that takes into account user preferences, comments in Kazakh language and likes to provide up-to-date book recommendations. The paper considers various methods of data collection, including the use of a telegram bot to generate comments in the Kazakh language and the collection of information from familiar users. Created a dataset containing 330 comments in Kazakh for model training and was divided into positive and negative comments using sentiment analysis methods. Various classification models were used for sentiment analysis, including Logistic Regression, Random Forest, Naive Bayes, and Support vector machine. The Support vector machine model achieved the highest accuracy of 95%, outperforming other models. In addition, the analysis of comments using histogram showed that positive comments usually contain more words than negative comments, which indicates more detailed and informative reviews. The identification of influential words and phrases provided insight into what aspects of books are valued by users. The developed recommendation system was integrated into the website of the online library. Two new users were created, who were given the opportunity to choose their preferred genres and languages. The system used the positive comments and likes associated with each book to generate personalized recommendations. This approach allows users to quickly find books they are interested in, which have already been popular and received positive feedback from other readers. arch has practical implications for developers of online libraries and other This rese platforms where personalized recommendations are required. The results and conclusions of this work can be used in the further development and improvement of recommendation systems, which will lead to an improvement in the quality of user service and an increase in their satisfaction.
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education, online library, Kazakh language, data collection