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Steam Recommendation System

05/03/2023

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by Samin Batra, et al.

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We aim to leverage the interactions between users and items in the Steam community to build a game recommendation system that makes personalized suggestions to players in order to boost Steam's revenue as well as improve the users' gaming experience. The whole project is built on Apache Spark and deals with Big Data. The final output of the project is a recommendation system that gives a list of the top 5 items that the users will possibly like.6

Samin Batra
1 publication
Varun Sharma
4 publications
Yurou Sun
1 publication
Xinyao Wang
7 publications
Yinyu Wang
1 publication

research

∙ 06/04/2017

Joint Text Embedding for Personalized Content-based Recommendation

Learning a good representation of text is key to many recommendation app...

0 Ting Chen, et al. ∙

research

∙ 12/25/2020

Dynamic-K Recommendation with Personalized Decision Boundary

In this paper, we investigate the recommendation task in the most common...

0 Yan Gao, et al. ∙

research

∙ 08/31/2018

Regularizing Matrix Factorization with User and Item Embeddings for Recommendation

Following recent successes in exploiting both latent factor and word emb...

0 Thanh Tran, et al. ∙

research

∙ 06/13/2018

A Machine-Learning Item Recommendation System for Video Games

Video-game players generate huge amounts of data, as everything they do ...

0 Paul Bertens, et al. ∙

research

∙ 07/13/2021

Sequential Recommendation for Cold-start Users with Meta Transitional Learning

A fundamental challenge for sequential recommenders is to capture the se...

0 Jianling Wang, et al. ∙

research

∙ 03/26/2021

Analysing the Effect of Recommendation Algorithms on the Amplification of Misinformation

Recommendation algorithms have been pointed out as one of the major culp...

0 Miriam Fernandez, et al. ∙

research

∙ 08/03/2021

Solving Fashion Recommendation – The Farfetch Challenge

Recommendation engines are integral to the modern e-commerce experience,...

3 Manish Pathak, et al. ∙