title: Ð Ð°Ð·ÑÐ°Ð±Ð¾ÑÐºÐ° Ð¸ ÑÐµÐ°Ð»Ð¸Ð·Ð°ÑÐ¸Ñ ÑÐµÐºÐ¾Ð¼ÐµÐ½Ð´Ð°ÑÐµÐ»ÑÐ½Ð¾Ð¹ ÑÐ¸ÑÑÐµÐ¼Ñ Ð´Ð»Ñ Ð¿ÐµÑÑÐ¾Ð½Ð°Ð»Ð¸Ð·Ð°ÑÐ¸Ð¸ Ð·Ð°Ð¿ÑÐ¾ÑÐ¾Ð² Ð¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°ÑÐµÐ»ÐµÐ¹ Ð¾Ð½Ð»Ð°Ð¹Ð½-ÑÐ¾ÑÐ³Ð¾Ð²Ð»Ð¸
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: Development and implementation of a recommendation system for personalizing the requests of online trading users
Creators: name: Ð¨ÐµÐ»ÑÐ³Ð¾Ð², Ð¡ÐµÑÐ³ÐµÐ¹
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: 2024
Subjects: Ð¾Ð½Ð»Ð°Ð¹Ð½-ÑÐ¾ÑÐ³Ð¾Ð²Ð»Ñ
ÑÐµÐºÐ¾Ð¼ÐµÐ½Ð´Ð°ÑÐµÐ»ÑÐ½ÑÐµ ÑÐ¸ÑÑÐµÐ¼Ñ
Ð¿ÐµÑÑÐ¾Ð½Ð°Ð»Ð¸Ð·Ð°ÑÐ¸Ñ
Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼Ñ ÑÐ¸Ð»ÑÑÑÐ°ÑÐ¸Ð¸
ÐºÐ¾Ð»Ð»Ð°Ð±Ð¾ÑÐ°ÑÐ¸Ð²Ð½Ð°Ñ ÑÐ¸Ð»ÑÑÑÐ°ÑÐ¸Ñ
ÐºÐ¾Ð½ÑÐµÐ½ÑÐ½Ð°Ñ ÑÐ¸Ð»ÑÑÑÐ°ÑÐ¸Ñ
Ð¾Ð¿ÑÐ¸Ð¼Ð¸Ð·Ð°ÑÐ¸Ñ Ð¿Ð¾Ð¸ÑÐºÐ°
Ð´Ð°Ð½Ð½ÑÐµ Ð¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°ÑÐµÐ»ÐµÐ¹
recommender systems
personalization
online trade
filtering algorithms
collaborative filtering
content filtering
search optimization
user data

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description: The goal of this work is to develop an effective recommendation system that allows you to personalize offers for users of online stores based on an analysis of their behavior and views. The work includes the study and application of modern algorithms for content filtering and collaborative filtering, searching and structuring data, selecting tools for system implementation, and developing models for adapting product offerings for the first time. The focus is on researching methods to optimize search for user queries and support quality recommendations by analyzing large volumes of data or improving the user experience, with Target increasing user satisfaction and loyalty, and increasing sales for online retailers. Thus, developing a recommender system is a complex task involving many steps and methods. The successful implementation of this work will significantly improve the user experience in online stores, increase the competitiveness of retailers and contribute to the development of data processing and analysis technologies.