Open AccessJournal Article
A Survey on Recommendation System for Big Data Applications
TLDR
The recommendation system related research is explained and different techniques used by the recommender system are introduced, which will give details about the main challenges recommender systems arrive across.Abstract:
Recommender systems is very useful tools for providing proper suggestions to users before buying any product online. Presently a days, the measure of users, services and online data has expands rapidly, accepting the enormous information investigation issue for recommender system. As a result, existing recommender systems have scalability and inefficiency issue when processing or analyzing extensive data, due to this distributed system come into existence. In this paper, explain the recommendation system related research and introduces different techniques used by the recommender system. Finally we will give details about the main challenges recommender systems arrive across.read more
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Adaptive Collaborative Filtering Based on Scalable Clustering for Big Recommender Systems
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Personalized recommendation based on preferential bidirectional mass diffusion
TL;DR: This work proposes a preferential bidirectional mass diffusion (PBMD) algorithm by penalizing the weight of popular objects in bid Directional diffusion, and results indicate that PBMD remarkably outperforms the mainstream methods in accuracy, diversity and novelty.