Introduction to Recommender Systems: Non-Personalized and Content-Based

课程

英语

12 时

来源

来自www.coursera.org

状况

自定进度
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4 序列
等级中级

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课程详情

教学大纲

Week 1 - Preface
This brief module introduces the topic of recommender systems (including placing the technology in historical context) and provides an overview of the structure and coverage of the course and specialization.
Week 1 - Introducing Recommender Systems
This module introduces recommender systems in more depth. It includes a detailed taxonomy of the types of recommender systems, and also includes tours of two systems heavily dependent on recommender technology: MovieLens and Amazon.com. There is an introduc...
Week 2 - Non-Personalized and Stereotype-Based Recommenders
In this module, you will learn several techniques for non- and lightly-personalized recommendations, including how to use meaningful summary statistics, how to compute product association recommendations, and how to explore using demographics as a means for li...
Week 3 - Content-Based Filtering -- Part I
The next topic in this course is content-based filtering, a technique for personalization based on building a profile of personal interests. Divided over two weeks, you will learn and practice the basic techniques for content-based filtering and then explore ...
Week 4 - Content-Based Filtering -- Part II
The assessments for content-based filtering include an assignment where you compute three types of profile and prediction using a spreadsheet and a quiz on the topics covered. The assignment is in three parts -- a written assignment, a video intro, and a "qui...
Week 4 - Course Wrap-up
We close this course with a set of mathematical notation that will be helpful as we move forward into a wider range of recommender systems (in later courses in this specialization).

先决条件

没有。

讲师

Joseph A Konstan
Distinguished McKnight Professor and Distinguished University Teaching Professor
Computer Science and Engineering

Michael D. Ekstrand
Assistant Professor
Dept. of Computer Science, Boise State University

编辑

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