Hybrid popularity model for solving cold-start problem in recommendation system

Ifada, Noor; Ummamah,; Kautsar, Mochammad

doi:10.1145/3427423.3427425

Cited by 2 publications

(1 citation statement)

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“…An ensemble model is proposed that combines Generalized Matrix Factorization (GMF) and Multi-Layer Perceptron (MLP) model to make predictions. Natarajan et al [15] proposed RS-LOD (Recommendation System with Linked Open Data) that uses a public interface cloud to solve cold start problem in collaborative filtering systems. To identify similar users Pearson's Correlation Coefficient is used.…”

Section: International Journal On Recent and Innovation Trends In Com...mentioning

confidence: 99%

A Deep Learning Approach towards Cold Start Problem in Movie Recommendation System

Panchal,

Vanjale

2023

IJRITCC

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Recommendation systems play an important role for e-commerce websites to make profits. It has a variety of applications in different domains. There are three types of categories in which recommendation systems are classified i.e. content based, collaborative and hybrid systems. These systems suffer when a redundant amount of information is not available to provide recommendations. This problem is known as the cold start problem. In this digital era, it is possible to collect meta information about a user and provide rich recommendations. Various approaches such as social media analysis, graph networks have been proposed to solve this problem. But they lack personalization and generate irrelevant recommendations affecting the system performance. The objective of this work is to resolve new user cold start problem in movie recommendation systems using a deep learning approach that utilizes demographic attributes to cluster similar users. This embedding is given to the deep neural network to generate the recommendations. From the analysis done, we verify the effectiveness of our approach..

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Section: International Journal On Recent and Innovation Trends In Com...mentioning

confidence: 99%