Java Programming: Build a Recommendation System

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课程主页: https://www.coursera.org/archive/java-programming-recommender

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Duke University

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You will start out the capstone project by taking a look at the features of a recommender engine. Then you will choose how to read in and organize user, ratings, and movie data in your program. The programming exercise will provide a check on your progress before moving on to the next step.

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Ever wonder how Netflix decides what movies to recommend for you? Or how Amazon recommends books? We can get a feel for how it works by building a simplified recommender of our own! In this capstone, you will show off your problem solving and Java programming skills by creating recommender systems. You will work with data for movies, including ratings, but the principles involved can easily be adapted to books, restaurants, and more. You will write a program to answer questions about the data, including which items should be recommended to a user based on their ratings of several movies. Given input files on users ratings and movie titles, you will be able to: 1. Read in and parse data into lists and maps; 2. Calculate average ratings; 3. Calculate how similar a given rater is to another user based on ratings; and 4. Recommend movies to a given user based on ratings. 5. Display recommended movies for a given user on a webpage.

Java编程:建立推荐系统:是否想过Netflix如何决定为您推荐什么电影?还是亚马逊如何推荐书籍?通过构建我们自己的简化推荐器,我们可以了解它的工作原理! 在此顶楼,您将通过创建推荐系统来展示您的问题解决能力和Java编程技能。您将使用电影数据(包括评级),但是所涉及的原理可以轻松地应用于书籍,餐厅等。您将编写一个程序来回答有关数据的问题,包括应根据用户对几部电影的评分向用户推荐哪些项目。给定用户评分和电影标题的输入文件,您将能够: 1.读入数据并将其解析为列表和地图; 2.计算平均收视率; 3.根据评分计算给定评分者与其他用户的相似程度;和 4.根据评级将电影推荐给给定的用户。 5.在网页上显示给定用户的推荐电影。

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