title: ÐÑÐ¸Ð¼ÐµÐ½ÐµÐ½Ð¸Ðµ Ð¼ÐµÑÐ¾Ð´Ð¾Ð² Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ð´Ð»Ñ ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐºÐ¸ ÑÐµÐºÐ¾Ð¼ÐµÐ½Ð´Ð°ÑÐµÐ»ÑÐ½Ð¾Ð¹ ÑÐ¸ÑÑÐµÐ¼Ñ Ð½Ð° Ð¾ÑÐ½Ð¾Ð²Ðµ Ð¾ÑÐµÐ½Ð¾Ðº Ð¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°ÑÐµÐ»ÐµÐ¹
title: Ð²ÑÐ¿ÑÑÐºÐ½Ð°Ñ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð¼Ð°Ð³Ð¸ÑÑÑÐ°
titleType: Subtitle
title: Applying machine learning methods to develop a recommendation system based on user ratings
Creators: name: ÐÐ°Ð»Ð¸Ñ, ÐÐ¸ÐºÑÐ¾ÑÐ¸Ñ
Publisher: name: Ð¡Ð°Ð½ÐºÑ-ÐÐµÑÐµÑÐ±ÑÑÐ³ÑÐºÐ¸Ð¹ Ð¿Ð¾Ð»Ð¸ÑÐµÑÐ½Ð¸ÑÐµÑÐºÐ¸Ð¹ ÑÐ½Ð¸Ð²ÐµÑÑÐ¸ÑÐµÑ ÐÐµÑÑÐ° ÐÐµÐ»Ð¸ÐºÐ¾Ð³Ð¾
Year: 2023
Subjects: ÑÐµÐºÐ¾Ð¼ÐµÐ½Ð´Ð°ÑÐµÐ»ÑÐ½Ð°Ñ ÑÐ¸ÑÑÐµÐ¼Ð°
ÑÐ¼ÐµÐ½ÑÑÐµÐ½Ð¸Ðµ ÑÐ°Ð·Ð¼ÐµÑÐ½Ð¾ÑÑÐ¸
ÑÐ¸Ð½Ð³ÑÐ»ÑÑÐ½Ð¾Ðµ ÑÐ°Ð·Ð»Ð¾Ð¶ÐµÐ½Ð¸Ðµ
ÑÑÐ¾Ñ Ð°ÑÑÐ¸ÑÐµÑÐºÐ¸Ð¹ Ð³ÑÐ°Ð´Ð¸ÐµÐ½ÑÐ½ÑÐ¹ ÑÐ¿ÑÑÐº
Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ðµ Ð¾Ð±ÑÑÐµÐ½Ð¸Ðµ
Ð°Ð½Ð°Ð»Ð¸Ð· Ð´Ð°Ð½Ð½ÑÑ
Telegram-Ð±Ð¾Ñ
recommendation system
dimensionality reduction
singular value decomposition
stochastic gradient descent
machine learning
data analysis
Telegram-bot

description: Ð¦ÐµÐ»Ñ Ð´Ð°Ð½Ð½Ð¾Ð¹ ÑÐ°Ð±Ð¾ÑÑ Ð·Ð°ÐºÐ»ÑÑÐ°ÐµÑÑÑ Ð² Ð°Ð½Ð°Ð»Ð¸Ð·Ðµ Ð¼ÐµÑÐ¾Ð´Ð¾Ð², Ð¿ÑÐ¸Ð¼ÐµÐ½ÑÐµÐ¼ÑÑ Ð´Ð»Ñ ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐºÐ¸ ÑÐµÐºÐ¾Ð¼ÐµÐ½Ð´Ð°ÑÐµÐ»ÑÐ½ÑÑ ÑÐ¸ÑÑÐµÐ¼, Ð¸ ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐºÐµ ÑÐ¾Ð±ÑÑÐ²ÐµÐ½Ð½Ð¾Ð¹ ÑÐ¸ÑÑÐµÐ¼Ñ Ð´Ð»Ñ ÑÐµÐºÐ¾Ð¼ÐµÐ½Ð´Ð°ÑÐ¸Ð¸ ÑÐ¸Ð»ÑÐ¼Ð¾Ð². Ð ÑÐ°Ð±Ð¾ÑÐµ ÑÐ°ÑÑÐ¼Ð°ÑÑÐ¸Ð²Ð°ÑÑÑÑ ÑÐ°Ð·Ð»Ð¸ÑÐ½ÑÐµ ÑÐ¸Ð¿Ñ ÑÐµÐºÐ¾Ð¼ÐµÐ½Ð´Ð°ÑÐµÐ»ÑÐ½ÑÑ ÑÐ¸ÑÑÐµÐ¼ Ð¸ Ð¼ÐµÑÐ¾Ð´Ñ Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ, Ð¸ÑÐ¿Ð¾Ð»ÑÐ·ÑÐµÐ¼ÑÐµ Ð² ÑÐµÐºÐ¾Ð¼ÐµÐ½Ð´Ð°ÑÐµÐ»ÑÐ½ÑÑ ÑÐ¸ÑÑÐµÐ¼Ð°Ñ. ÐÐ»Ñ ÑÐ¾Ð·Ð´Ð°Ð½Ð¸Ñ ÐºÐ¾Ð»Ð»Ð°Ð±Ð¾ÑÐ°ÑÐ¸Ð²Ð½Ð¾Ð¹ ÑÐ¸ÑÑÐµÐ¼Ñ ÑÐµÐºÐ¾Ð¼ÐµÐ½Ð´Ð°ÑÐ¸Ð¹ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·ÑÑÑÑÑ ÑÐ°ÐºÐ¸Ðµ Ð¼ÐµÑÐ¾Ð´Ñ, ÐºÐ°Ðº ÑÐ¸Ð½Ð³ÑÐ»ÑÑÐ½Ð¾Ðµ ÑÐ°Ð·Ð»Ð¾Ð¶ÐµÐ½Ð¸Ðµ, ÑÑÐ¾ÑÐ°ÑÑÐ¸ÑÐµÑÐºÐ¸Ð¹ Ð³ÑÐ°Ð´Ð¸ÐµÐ½ÑÐ½ÑÐ¹ ÑÐ¿ÑÑÐº Ñ Ð¿ÑÐ¸Ð¼ÐµÐ½ÐµÐ½Ð¸ÐµÐ¼ ÑÐµÐ³ÑÐ»ÑÑÐ¸Ð·Ð°ÑÐ¾ÑÐ° Ð¸ Ð´Ð¾Ð±Ð°Ð²Ð»ÐµÐ½Ð¸ÐµÐ¼ Ð¸Ð¼Ð¿ÑÐ»ÑÑÐ°. ÐÐ»Ñ ÑÐµÑÐµÐ½Ð¸Ñ Ð¿ÑÐ¾Ð±Ð»ÐµÐ¼Ñ ÑÐ¾Ð»Ð¾Ð´Ð½Ð¾Ð³Ð¾ ÑÑÐ°ÑÑÐ° Ð¸ ÑÐ¾Ð·Ð´Ð°Ð½Ð¸Ñ ÑÐ¸ÑÑÐµÐ¼Ñ, Ð¾ÑÐ½Ð¾Ð²Ð°Ð½Ð½Ð¾Ð¹ Ð½Ð° ÑÐ¾Ð´ÐµÑÐ¶Ð°Ð½Ð¸Ð¸, Ð¿ÑÐ¾Ð²Ð¾Ð´Ð¸ÑÑÑ Ð°Ð½Ð°Ð»Ð¸Ð· Ð¶Ð°Ð½ÑÐ¾Ð² ÑÐ¸Ð»ÑÐ¼Ð¾Ð² Ñ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð½Ð¸ÐµÐ¼ Ð¼ÐµÑÐ¾Ð´Ð° TF-IDF. ÐÐ¾Ð»ÑÑÐµÐ½Ð½ÑÐµ Ð·Ð½Ð°ÑÐµÐ½Ð¸Ñ Ð¾Ð±ÑÐ°Ð±Ð°ÑÑÐ²Ð°ÑÑÑÑ Ð¼ÐµÑÐ¾Ð´Ð¾Ð¼ Ð±Ð»Ð¸Ð¶Ð°Ð¹ÑÐ¸Ñ ÑÐ¾ÑÐµÐ´ÐµÐ¹, ÑÑÐ¾ Ð¿Ð¾Ð·Ð²Ð¾Ð»ÑÐµÑ ÑÑÐµÑÑÑ Ð¿ÑÐµÐ´Ð¿Ð¾ÑÑÐµÐ½Ð¸Ñ Ð¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°ÑÐµÐ»ÐµÐ¹. Ð¢Ð¾ÑÐ½Ð¾ÑÑÑ ÐºÐ°Ð¶Ð´Ð¾Ð³Ð¾ ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐ°Ð½Ð½Ð¾Ð³Ð¾ Ð¼ÐµÑÐ¾Ð´Ð° Ð¿ÑÐ¾Ð²ÐµÑÑÐµÑÑÑ Ð½Ð° ÑÐµÐ³ÑÐµÑÑÐ¸Ð¾Ð½Ð½ÑÑ Ð¼ÐµÑÑÐ¸ÐºÐ°Ñ: ÑÑÐµÐ´Ð½ÐµÐºÐ²Ð°Ð´ÑÐ°ÑÐ¸ÑÐ½Ð¾Ðµ Ð¾ÑÐºÐ»Ð¾Ð½ÐµÐ½Ð¸Ðµ, ÐºÐ¾ÑÐµÐ½Ñ Ð¸Ð· ÑÑÐµÐ´Ð½ÐµÐºÐ²Ð°Ð´ÑÐ°ÑÐ¸ÑÐ½Ð¾Ð³Ð¾ Ð¾ÑÐºÐ»Ð¾Ð½ÐµÐ½Ð¸Ñ, ÑÑÐµÐ´Ð½ÐµÐµ Ð°Ð±ÑÐ¾Ð»ÑÑÐ½Ð¾Ðµ Ð¾ÑÐºÐ»Ð¾Ð½ÐµÐ½Ð¸Ðµ. Ð ÑÐ°Ð¼ÐºÐ°Ñ ÑÐ°Ð±Ð¾ÑÑ ÑÐ¾Ð·Ð´Ð°ÐµÑÑÑ Ð±Ð°Ð·Ð° Ð´Ð°Ð½Ð½ÑÑ, Ð² ÐºÐ¾ÑÐ¾ÑÐ¾Ð¹ ÑÑÐ°Ð½Ð¸ÑÑÑ Ð¸Ð½ÑÐ¾ÑÐ¼Ð°ÑÐ¸Ñ Ñ Ð¾ÑÐµÐ½ÐºÐ°Ð¼Ð¸ Ð¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°ÑÐµÐ»ÐµÐ¹, Ð¸ ÑÐ°Ð·ÑÐ°Ð±Ð°ÑÑÐ²Ð°ÐµÑÑÑ telegram-Ð±Ð¾Ñ, Ð² ÐºÐ¾ÑÐ¾ÑÐ¾Ð¼ ÐºÐ¾Ð¼Ð±Ð¸Ð½Ð¸ÑÑÑÑÑÑ ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐ°Ð½Ð½ÑÐµ Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼Ñ Ð¸ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·ÑÑÑÑÑ Ð´Ð»Ñ ÑÐ¾Ð·Ð´Ð°Ð½Ð¸Ñ Ð¿ÐµÑÑÐ¾Ð½Ð°Ð»Ð¸Ð·Ð¸ÑÐ¾Ð²Ð°Ð½Ð½ÑÑ ÑÐµÐºÐ¾Ð¼ÐµÐ½Ð´Ð°ÑÐ¸Ð¹ ÑÐ¸Ð»ÑÐ¼Ð¾Ð².
description: The aim of this thesis is to analyze the methods that are used to develop recommendation systems, and to develop my own system for movie recommendation. The paper examines different types of recommender systems and the machine learning techniques used in recommender systems. Methods such as singular decomposition, stochastic gradient descent with regularizer application and momentum addition are used to design a collaborative recommendation system. In order to solve the problem of cold start and create a content-based system, movie genres are analyzed using TF-IDF method. The resulting values are processed using the nearest neighbour method, which allows user preferences to be taken into account. The accuracy of each developed method is tested on regression metrics: mean squared error, root mean squared error, mean absolute error. As part of the work, a database is created to store information with user ratings, and a telegram-bot is developed that combines the developed algorithms and is used to create personalized movie recommendations.