Sequential Recommendation Using Convolutional Neural Networks

الموضوعات

علوم تطبيقية وتكنولوجية

الملخص

With the prevalence of information technology (IT), recommender system has long been acknowledged as an effective tool for addressing information overload problem, whichmakes users easily filter and locate information of their preferences, and allows online platforms to widely publicize the information they produce. In the field of sequential recommendation, deep learning methods have received a lot of attention in the past few years and surpassed traditional models such as Markov chain-based andfactorization-based ones. In this view, this thesis focuses on DL-based sequential recommender systems by taking the aforementioned issues into consideration. Specifically,we illustrate the concept of sequential recommendation, propose a convolutional neural network model to show the effectiveness of sequential recommenders based on CNNs in several real-life scenarios.

روابط وملفات

التعريف والنوع

رقم الوثيقة

fa470ce0-cd1b-44f2-b6f3-ca2d72b83076

رقم العقد

0

نوع الوسائط

Crawler

نوع المحتوى

الرسائل العلمية

صيغة المصدر

ماستر (LMD)

نوع الملف

pdf text

أسماء الملفات

2259243_1.pdf

بيانات النشر

ألقاب المؤلفين

[{"name_ar":"Boudjemaa Boudaa","title_ar":"اشراف","title_en":"Supervision"},{"name_ar":"Boutheina Cherfi","title_ar":"اعداد","title_en":"Preparation"}]

اللغة

English

المصدر والدورية

اسم المصدر

Sequential Recommendation Using Convolutional Neural Networks

المحتوى والصفحات

عدد الصفحات

0

كلمات الباحثين

Recommender systems, Sequential Recommendation, Sequential data, Neural networks, Convolutional neural networks, Next-Item recommendation.

إشراف وإعداد

الإشراف

Boudjemaa Boudaa

الإعداد

Boutheina Cherfi

الاقتباسات الببليوغرافية