Escaping the echo chamber in movies recommender system

الموضوعات

علوم تطبيقية وتكنولوجية

الملخص

With the considerable rise of Internet users and the massive and diverse web searches, an excess of data has become available online. A recommendation model, also known as an engine, handles this massive amount of data available to find patterns that reflect user behaviors. Recommendation models have been implemented in several industries, and the most popular implementation is in the entertainment industry, specifically video streaming and on-demand platforms. There are several types of recommendation systems. In this paper, we have proposed a way to escape the loop created by the recommendation systems, where, the more “same genre” movie we watch, the more of that same genre the recommendation system will propose.

روابط وملفات

التعريف والنوع

رقم الوثيقة

eeb35ecf-be20-47ba-8804-d6f0784a5b97

رقم العقد

0

نوع الوسائط

Crawler

نوع المحتوى

الرسائل العلمية

صيغة المصدر

رسائل ماجيستير

نوع الملف

pdf text

أسماء الملفات

2295845_1.pdf

بيانات النشر

ألقاب المؤلفين

[{"name_ar":"El Haddad Anthony","title_ar":"اعداد","title_en":"Preparation"},{"name_ar":"هدى معلوف","title_ar":"اشراف","title_en":"Supervision"}]

اللغة

English

المصدر والدورية

اسم المصدر

Escaping the echo chamber in movies recommender system

المحتوى والصفحات

عدد الصفحات

0

كلمات الباحثين

Filter bubbles (Information filtering) Recommender systems (Information filtering) Machine learning

إشراف وإعداد

الإشراف

هدى معلوف

الإعداد

El Haddad Anthony

الاقتباسات الببليوغرافية