title: Ð ÐµÐºÐ¾Ð¼ÐµÐ½Ð´Ð°ÑÐµÐ»ÑÐ½Ð°Ñ ÑÐ¸ÑÑÐµÐ¼Ð° Ð½Ð° Ð¾ÑÐ½Ð¾Ð²Ðµ ÐºÐ¾Ð»Ð»Ð°Ð±Ð¾ÑÐ°ÑÐ¸Ð²Ð½Ð¾Ð¹ ÑÐ¸Ð»ÑÑÑÐ°ÑÐ¸Ð¸
title: Ð²ÑÐ¿ÑÑÐºÐ½Ð°Ñ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð±Ð°ÐºÐ°Ð»Ð°Ð²ÑÐ°
titleType: Subtitle
title: Recommender system based on collaborative filtering
Creators: name: ÐÐ°Ð½ÑÑ, ÐÑÐ¸ÑÑÐ¸Ð½Ð°
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°
ÐºÐ¾Ð»Ð»Ð°Ð±Ð¾ÑÐ°ÑÐ¸Ð²Ð½Ð°Ñ ÑÐ¸Ð»ÑÑÑÐ°ÑÐ¸Ñ
ÑÐ·ÑÐº Python
Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ðµ Ð¾Ð±ÑÑÐµÐ½Ð¸Ðµ
Ð¼ÐµÑÐ¾Ð´ Leave-one-out
recommender system
collaborative filtering
Python language
machine learning
Leave-one-out method

description: ÐÐ°Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð¿Ð¾ÑÐ²ÑÑÐµÐ½Ð° ÑÐ¾Ð·Ð´Ð°Ð½Ð¸Ñ ÑÐµÐºÐ¾Ð¼ÐµÐ½Ð´Ð°ÑÐµÐ»ÑÐ½Ð¾Ð¹ ÑÐ¸ÑÑÐµÐ¼Ñ, Ð¸ÑÐ¿Ð¾Ð»ÑÐ·ÑÑ Ð´Ð°Ð½Ð½ÑÐµ Ð¾ 20 Ð¼Ð¸Ð»Ð»Ð¸Ð¾Ð½Ð°Ñ Ð¾ÑÐµÐ½Ð¾Ðº ÑÐ¸Ð»ÑÐ¼Ð¾Ð² Ñ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð½Ð¸ÐµÐ¼ Ð¼ÐµÑÐ¾Ð´Ð° ÐºÐ¾Ð»Ð»Ð°Ð±Ð¾ÑÐ°ÑÐ¸Ð²Ð½Ð¾Ð¹ ÑÐ¸Ð»ÑÑÑÐ°ÑÐ¸Ð¸ Ñ Ð¿Ð¾Ð¼Ð¾ÑÑÑ ÑÐ·ÑÐºÐ° Python. ÐÐ°Ð´Ð°ÑÐ¸, ÐºÐ¾ÑÐ¾ÑÑÐµ ÑÐµÑÐ°Ð»Ð¸ÑÑ Ð² ÑÐ¾Ð´Ðµ Ð²ÑÐ¿Ð¾Ð»Ð½ÐµÐ½Ð¸Ñ ÑÐ°Ð±Ð¾ÑÑ: 1) ÐÐ·ÑÑÐµÐ½Ð¸Ðµ Ð¼ÐµÑÐ¾Ð´Ð° ÐºÐ¾Ð»Ð»Ð°Ð±Ð¾ÑÐ°ÑÐ¸Ð²Ð½Ð¾Ð¹ ÑÐ¸Ð»ÑÑÑÐ°ÑÐ¸Ð¸; 2) ÐÑÐ±Ð¾Ñ Ð¿ÑÐ¾Ð³ÑÐ°Ð¼Ð¼Ð½ÑÑ ÑÑÐµÐ´ÑÑÐ² Ð´Ð»Ñ ÑÐµÐ°Ð»Ð¸Ð·Ð°ÑÐ¸Ð¸ ÑÐµÐºÐ¾Ð¼ÐµÐ½Ð´Ð°ÑÐµÐ»ÑÐ½Ð¾Ð¹ ÑÐ¸ÑÑÐµÐ¼Ñ; 3) ÐÐ·ÑÑÐµÐ½Ð¸Ðµ Ð´Ð°Ð½Ð½ÑÑ; 4) ÐÐ¾Ð´Ð³Ð¾ÑÐ¾Ð²ÐºÐ° Ð´Ð°Ð½Ð½ÑÑ; 5) Ð¡Ð¾Ð·Ð´Ð°Ð½Ð¸Ðµ ÑÐµÐºÐ¾Ð¼ÐµÐ½Ð´Ð°ÑÐµÐ»ÑÐ½Ð¾Ð¹ ÑÐ¸ÑÑÐµÐ¼Ñ; 6) ÐÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ðµ ÑÑÑÐ¾Ð¹ÑÐ¸Ð²Ð¾ÑÑÐ¸ ÑÐµÐºÐ¾Ð¼ÐµÐ½Ð´Ð°ÑÐµÐ»ÑÐ½Ð¾Ð¹ ÑÐ¸ÑÑÐµÐ¼Ñ Ð¼ÐµÑÐ¾Ð´Ð¾Ð¼ leave-one-out. Ð ÑÐ¾Ð´Ðµ ÑÐ°Ð±Ð¾ÑÑ Ð±ÑÐ»Ð¸ Ð¸Ð·ÑÑÐµÐ½Ñ Ð¼ÐµÑÐ¾Ð´Ñ ÑÐµÐºÐ¾Ð¼ÐµÐ½Ð´Ð°ÑÐµÐ»ÑÐ½ÑÑ ÑÐ¸ÑÑÐµÐ¼: ÑÐ¸Ð»ÑÑÑÐ°ÑÐ¸Ñ Ð½Ð° Ð¾ÑÐ½Ð¾Ð²Ðµ ÑÐ¾Ð´ÐµÑÐ¶Ð°Ð½Ð¸Ñ, ÐºÐ¾Ð»Ð»Ð°Ð±Ð¾ÑÐ°ÑÐ¸Ð²Ð½Ð°Ñ ÑÐ¸Ð»ÑÑÑÐ°ÑÐ¸Ñ Ð¸ Ð³Ð¸Ð±ÑÐ¸Ð´Ð½Ð°Ñ ÑÐ¸ÑÑÐµÐ¼Ð°. Ð¢Ð°ÐºÐ¶Ðµ Ð±ÑÐ» Ð¾Ð¿Ð¸ÑÐ°Ð½ Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼ Ð¼ÐµÑÐ¾Ð´Ð° ÐºÐ¾Ð»Ð»Ð°Ð±Ð¾ÑÐ°ÑÐ¸Ð²Ð½Ð¾Ð¹ ÑÐ¸Ð»ÑÑÑÐ°ÑÐ¸Ð¸. Ð¡ Ð¿Ð¾Ð¼Ð¾ÑÑÑ ÑÐ·ÑÐºÐ° Python Ð±ÑÐ»Ð° ÑÐ¾Ð·Ð´Ð°Ð½Ð° ÑÐµÐºÐ¾Ð¼ÐµÐ½Ð´Ð°ÑÐµÐ»ÑÐ½Ð°Ñ ÑÐ¸ÑÑÐµÐ¼Ð° Ð½Ð° Ð¾ÑÐ½Ð¾Ð²Ðµ ÐºÐ¾Ð»Ð»Ð°Ð±Ð¾ÑÐ°ÑÐ¸Ð²Ð½Ð¾Ð¹ ÑÐ¸Ð»ÑÑÑÐ°ÑÐ¸Ð¸, ÑÐ°ÐºÐ¶Ðµ Ñ Ð¿Ð¾Ð¼Ð¾ÑÑÑ Ð±Ð¸Ð±Ð»Ð¸Ð¾ÑÐµÐºÐ¸ scikit-learn ÑÐ·ÑÐºÐ° Python Ð±ÑÐ»Ð¾ Ð¿ÑÐ¾Ð²ÐµÐ´ÐµÐ½Ð¾ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ðµ ÐºÐ°ÑÐµÑÑÐ²Ð° ÑÐ¸ÑÑÐµÐ¼Ñ Ð¼ÐµÑÐ¾Ð´Ð¾Ð¼ leave-one-out. Ð ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÐµ Ð±ÑÐ»Ð° ÑÐ¾Ð·Ð´Ð°Ð½Ð° ÑÐµÐºÐ¾Ð¼ÐµÐ½Ð´Ð°ÑÐµÐ»ÑÐ½Ð°Ñ ÑÐ¸ÑÑÐµÐ¼Ð° Ð½Ð° Ð¾ÑÐ½Ð¾Ð²Ðµ Ð¼ÐµÑÐ¾Ð´Ð° ÐºÐ¾Ð»Ð»Ð°Ð±Ð¾ÑÐ°ÑÐ¸Ð²Ð½Ð¾Ð¹ ÑÐ¸Ð»ÑÑÑÐ°ÑÐ¸Ð¸ Ð¸ ÑÐ´ÐµÐ»Ð°Ð½ Ð²ÑÐ²Ð¾Ð´ Ð¾Ð± ÐµÑ ÐºÐ°ÑÐµÑÑÐ²Ðµ.
description: This work is devoted to the construction of recommendations based on twenty million movie ratings using collaborative filtering method using Python. The tasks that were solved in the course of the work were: 1) Study the collaborative filtering method 2) Selection of software tools to implement the recommender system 3) Researching the data 4) Data preparation 5) Creation of the recommender system 6) Study of the stability of the recommender system by the leave-one-out method. In the course of this work, the methods of recommender systems was studied: content-based filtering, collaborative filtering, and hybrid system. The algorithm for the collaborative filtering method was also described. A collaborative filtering-based recommender system was created using the Python language, and the systems quality was investigated using the scikit-learn library of Python using the leave-one-out method. As a result, a recommender system based on the collaborative filtering was created and a conclusion about its quality was made.