RiVal recommender system evaluation toolkit
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Updated
Jan 30, 2019 - Java
RiVal recommender system evaluation toolkit
Personalized real-time movie recommendation system
A simple movie recommendation api using apache mahout machine learning library.
Mining and Utilizing Dataset Relevancy from Oceanographic Datasets to Improve Data Discovery and Access, online demo: https://mudrod.jpl.nasa.gov/#/
This is a personalization-based event recommendation systems for event search.
Recommendation engine in Java. Based on an ALS algorithm (Apache Spark). Train a new model after N seconds.
基于 Spark Streaming 的电影推荐系统
Intellij plugin development to source-code recommendation
A JavaFX music recommendation app that uses the Spotify API to create playlists.
Book Recommendation Service
基于 Spark 的微服务推荐系统
Movie / Film recommendation system built using Java utilizing knowledge graph technology.
A Hybrid Recommendation model based on sentiment analysis on tweets and item based filtering to closely match preferred recommendation.
Shopping-buster app powered by Content Based Recommendation engine.
A Java console application that implements the factionality of the knn algorithm to find the similarity between a new user with only a few non zero ratings of some locations, find the k nearest neighbors through similarity score and then predict the ratings of the new user for the non rated locations.
Movie Recommendations like Netflix, Amezon Prime
GUI to help automate functions of the LibRec Java recommendation systems library
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