title: Ð Ð°Ð·ÑÐ°Ð±Ð¾ÑÐºÐ° Ð¼Ð¾Ð±Ð¸Ð»ÑÐ½Ð¾Ð³Ð¾ Ð¿ÑÐ¸Ð»Ð¾Ð¶ÐµÐ½Ð¸Ñ Ð´Ð»Ñ Ð¿Ð¾Ð¸ÑÐºÐ° ÑÐµÐ»ÐµÐ²Ð¾Ð³Ð¾ ÐºÐ¾Ð½ÑÐµÐ½Ñ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: Developing a mobile application to search for targeted content
Creators: name: ÐÐ±ÑÐ»ÐºÐ°ÑÑÐ¼Ð¾Ð²Ð°, ÐÑÐµÐ»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: 2020
Subjects: ÑÐµÐºÐ¾Ð¼ÐµÐ½Ð´Ð°ÑÐµÐ»ÑÐ½ÑÐµ ÑÐ¸ÑÑÐµÐ¼Ñ
Ñ Ð¾Ð»Ð¾Ð´Ð½ÑÐ¹ ÑÑÐ°ÑÑ
Ð¼ÐµÑÐ¾Ð´ ÑÐµÑÐµÐ´ÑÑÑÐ¸Ñ ÑÑ Ð½Ð°Ð¸Ð¼ÐµÐ½ÑÑÐ¸Ñ ÐºÐ²Ð°Ð´ÑÐ°ÑÐ¾Ð²
Ð±Ð¾Ð»ÑÑÐ¸Ðµ Ð´Ð°Ð½Ð½ÑÐµ
recommender systems
cold start
alternated least square method
big data

description: Ð¦ÐµÐ»Ñ ÑÐ°Ð±Ð¾ÑÑ Ð·Ð°ÐºÐ»ÑÑÐ°ÐµÑÑÑ Ð² ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐºÐµ Ð¼Ð¾Ð±Ð¸Ð»ÑÐ½Ð¾Ð³Ð¾ Android-Ð¿ÑÐ¸Ð»Ð¾Ð¶ÐµÐ½Ð¸Ñ Ð´Ð»Ñ Ð¸Ð½ÑÐµÐ³ÑÐ°ÑÐ¸Ð¸ Ñ ÑÐµÐºÐ¾Ð¼ÐµÐ½Ð´Ð°ÑÐµÐ»ÑÐ½Ð¾Ð¹ ÑÐ¸Ñ-ÑÐµÐ¼Ð¾Ð¹ Ð¿Ð¾Ð´Ð±Ð¾ÑÐ° ÑÐµÐ»ÐµÐ²Ð¾Ð³Ð¾ ÐºÐ¾Ð½ÑÐµÐ½ÑÐ°, Ð¾ÑÐ½Ð¾Ð²Ð°Ð½Ð½Ð¾Ð¹ Ð½Ð° Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼Ðµ BALSE, Ð¼Ð¾Ð´ÐµÐ»Ñ Ð´Ð»Ñ ÑÐµÐºÐ¾Ð¼ÐµÐ½Ð´Ð°ÑÐ¸Ð¸ Ð°Ð½Ð¸Ð¼Ðµ Ð¸ Ð¼Ð°Ð½Ð³Ð¸, ÐºÐ¾ÑÐ¾ÑÐ°Ñ Ð¸Ñ-Ð¿Ð¾Ð»ÑÐ·ÑÐµÑ Ð¸Ð½ÑÐ¾ÑÐ¼Ð°ÑÐ¸Ñ, Ð°Ð²ÑÐ¾Ð¼Ð°ÑÐ¸ÑÐµÑÐºÐ¸ Ð¸Ð·Ð²Ð»ÐµÐºÐ°ÑÑÐ°ÑÑÑ Ð¸Ð· Ð¿Ð¾ÑÑÐµ-ÑÐ¾Ð², Ð´Ð»ÑÑÐµÐ»ÐµÐ²Ð°Ð½ÑÐ½Ð¾Ð³Ð¾ Ð¾ÑÐ¾Ð±ÑÐ°Ð¶ÐµÐ½Ð¸Ñ Ð½Ð° ÑÐºÑÐ°Ð½Ðµ Ð¼Ð¾Ð±Ð¸Ð»ÑÐ½Ð¾Ð³Ð¾ ÑÑÑ-ÑÐ¾Ð¹ÑÑÐ²Ð°. ÐÐºÑÑÐ°Ð»ÑÐ½Ð¾ÑÑÑ ÑÐµÐ¼Ñ Ð¾Ð±ÑÑÐ»Ð¾Ð²Ð»ÐµÐ½Ð° Ð³ÑÐ¾Ð¼Ð°Ð´Ð½ÑÐ¼Ð¸ ÑÐµÐ¼Ð¿Ð°Ð¼Ð¸ ÑÐ¾ÑÑÐ° Ð¿Ð¾Ð¿ÑÐ»ÑÑÐ½Ð¾ÑÑÐ¸ Ð°Ð½Ð¸Ð¼Ðµ Ð¸ Ð¼Ð°Ð½Ð³Ð¸ Ð·Ð° Ð¿ÑÐµÐ´ÐµÐ»Ð°Ð¼Ð¸ Ð¯Ð¿Ð¾Ð½Ð¸Ð¸, Ð° ÑÐ°Ðº-Ð¶Ðµ Ð¿Ð¾ÑÐ²Ð»ÐµÐ½Ð¸ÐµÐ¼ ÑÐ°Ð¹ÑÐ¾Ð²-Ð°Ð³ÑÐµÐ³Ð°ÑÐ¾ÑÐ¾Ð² Ñ Ð¾ÑÐºÑÑÑÑÐ¼Ð¸ Ð±Ð°Ð·Ð°Ð¼Ð¸ Ð´Ð°Ð½Ð½ÑÑ, ÑÑÐ¾ Ð¾Ð±Ð»ÐµÐ³ÑÐ¸Ð»Ð¾ ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐºÑ Ð¸ ÑÐµÑÑÐ¸ÑÐ¾Ð²Ð°Ð½Ð¸Ðµ ÑÐ°Ð·Ð»Ð¸ÑÐ½ÑÑ Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼Ð¾Ð² Ð¸ Ð¿Ð¾Ð´ÑÐ¾Ð´Ð¾Ð¼ Ð´Ð»Ñ Ð¿Ð¾ÑÑÑÐ¾ÐµÐ½Ð¸Ñ ÑÐµÐºÐ¾Ð¼ÐµÐ½Ð´Ð°ÑÐµÐ»ÑÐ½ÑÑ ÑÐ¸ÑÑÐµÐ¼. ÐÑÐ½Ð¾Ð²Ð½ÑÐ¼ Ð½ÐµÐ´Ð¾ÑÑÐ°ÑÐºÐ¾Ð¼ Ð¿Ð¾Ð´Ð¾Ð±Ð½ÑÑ Ð¼ÐµÑÐ¾Ð´Ð¾Ð² ÑÐ²Ð»ÑÐµÑÑÑ Ð½ÐµÐ¾Ð±ÑÐ¾Ð´Ð¸-Ð¼Ð¾ÑÑÑ Ð´Ð¾Ð¿Ð¾Ð»Ð½Ð¸ÑÐµÐ»ÑÐ½Ð¾Ð¹ Ð¸Ð½ÑÐ¾ÑÐ¼Ð°ÑÐ¸Ð¸, ÐºÐ¾ÑÐ¾ÑÑÑ Ð¾Ð±ÑÑÐ½Ð¾ Ð´Ð¾ÑÐ¾Ð³Ð¾ Ð¸ Ð´Ð¾Ð»Ð³Ð¾ ÑÐ¾Ð±Ð¸ÑÐ°ÑÑ. ÐÑÐ» Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð½ Ð³Ð¾ÑÐ¾Ð²ÑÐ¹ Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼ ÑÐµÐºÐ¾Ð¼ÐµÐ½Ð´Ð°-ÑÐ¸Ð¹ Ð´Ð»Ñ ÑÐ¾Ð·Ð´Ð°Ð½Ð¸Ñ Ð¿ÑÐ¸Ð»Ð¾Ð¶ÐµÐ½Ð¸Ñ ÑÐ°Ð¹ÑÐ°. ÐÑÐ¸Ð»Ð¾Ð¶ÐµÐ½Ð¸Ðµ ÑÐµÐ°Ð»Ð¸Ð·Ð¾Ð²Ð°Ð½Ð¾ Ð½Ð° ÑÐ·ÑÐºÐµ Java Android Studio Ñ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð½Ð¸ÐµÐ¼ Ð±Ð¸Ð±Ð»Ð¸Ð¾ÑÐµÐº okhttp3 Ð¸ retrofit.
ÐÐ±ÑÐµÐºÑÐ¾Ð¼ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ñ ÑÐ²Ð»ÑÑÑÑÑ ÑÐµÐºÐ¾Ð¼ÐµÐ½Ð´Ð°ÑÐµÐ»ÑÐ½ÑÐµ ÑÐ¸Ñ-ÑÐµÐ¼Ñ Ð¿Ð¾ Ð¿Ð¾Ð´Ð±Ð¾ÑÑ ÑÐµÐ»ÐµÐ²Ð¾Ð³Ð¾ ÐºÐ¾Ð½ÑÐµÐ½ÑÐ°. Ð¨Ð¸ÑÐ¾ÐºÐ¸Ð¼ Ð°Ð³ÑÐµÐ³Ð°ÑÐ¾ÑÐ¾Ð¼ Ð´Ð°Ð½Ð½ÑÑ, ÐºÐ¾ÑÐ¾ÑÑÐµ Ð¿Ð¾Ð·Ð²Ð¾Ð»ÑÑÑ ÑÐ¾Ð·Ð´Ð°Ð²Ð°ÑÑ Ð¼Ð¾Ð´ÐµÐ»Ð¸ Ð´Ð´Ñ Ð´Ð°Ð»ÑÐ½ÐµÐ¹ÑÐµÐ¹ ÑÐµÐºÐ¾Ð¼ÐµÐ½Ð´Ð°ÑÐµÐ»ÑÐ½Ð¾Ð¹ ÑÐ¸ÑÑÐµÐ¼Ñ.
ÐÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ñ Ð²Ð¸Ð´Ñ ÑÐµÐºÐ¾Ð¼ÐµÐ½Ð´Ð°ÑÐµÐ»ÑÐ½ÑÑ ÑÐ¸ÑÑÐµÐ¼ Ð¸ Ð¿ÑÐ¸Ð½ÑÐ¸Ð¿Ñ Ð¸Ñ Ð¿Ð¾ÑÑÑÐ¾ÐµÐ½Ð¸Ñ. ÐÐ·ÑÑÐµÐ½Ð° Ð¼Ð°ÑÑÐ¸ÑÐ½Ð°Ñ ÑÐ°ÐºÑÐ¾ÑÐ¸Ð·Ð°ÑÐ¸Ñ Ð¸ Ð¼ÐµÑÐ¾Ð´ Ð½Ð°Ð¸-Ð¼ÐµÐ½ÑÑÐ¸Ñ ÑÐµÑÐµÐ´ÑÑÑÐ¸ÑÑÑ ÐºÐ²Ð°Ð´ÑÐ°ÑÐ¾Ð². ÐÐ° Ð¾ÑÐ½Ð¾Ð²Ðµ Ð¼ÐµÑÐ¾Ð´Ð° ÑÐµÑÐµÐ´ÑÑ-ÑÐ¸ÑÑÑ Ð½Ð°Ð¸Ð¼ÐµÐ½ÑÑÐ¸Ñ ÐºÐ²Ð°Ð´ÑÐ°ÑÐ¾Ð² ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐ°Ð½Ð° ÑÐµÐºÐ¾Ð¼ÐµÐ½Ð´Ð°ÑÐµÐ»ÑÐ½Ð°Ñ ÑÐ¸ÑÑÐµÐ¼Ð° Ð´Ð»Ñ ÑÐµÐ»ÐµÐ²Ð¾Ð³Ð¾ ÐºÐ¾Ð½ÑÐµÐ½ÑÐ°.
description: The purpose of the work is to develop a mobile Android ap-plication for integration with a recommendation system for target content selection based on the BALSE algorithm, a model for re-commending anime and manga that uses information automatically extracted from posters for relevant display on a mobile screen devic-es. The relevance of the topic is due to the huge growth rates of anime and manga outside of Japan, as well as the emergence of ag-gregator sites with open databases, which facilitated the development and testing of various algorithms and the approach to building rec-ommendation systems. The main disadvantage of such methods is the need for additional information, which is usually expensive and time consuming to collect. A ready-made recommendation algorithm was used to create the site application. The application is implemented in the Java language Android Studio using the okhttp3 and retrofit libraries.
The object of the study are recommendation systems for the selection of targeted content. A wide data aggregator that allows you to create models for the future recommender system.
The types of recommendation systems and the principles of their construction are investigated. The matrix factorization and the method of least alternating squares are studied. Based on the method of alternating least squares, a recommendation system for target con-tent has been developed.