학술논문

Steam Recommendation System
Document Type
Working Paper
Source
Subject
Computer Science - Information Retrieval
Language
Abstract
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
Comment: 6 pages, 7 figures, 8 tables