Lecture 4: Social and Hybrid Filters

It’s possible to build powerful filtering systems by combining software and people, incorporating both algorithmic content analysis and human actions such as follow, share, and like. We’ll look recommendation systems, the Facebook news feed, and the socially-driven algorithms behind them. We’ll finish by looking at an example of using human preferences to drive machine learning algorithms: Google Web search.

Topics: Social filtering. The network structure of Twitter. Social software. Comment ranking on Reddit. Confidence sorting. User-item recommendation and collaborative filtering. Hybrid filters. What makes a good filter?

Slides (PDF)

Readings

Recommended

Assignment: Hybrid filter Design. Design a filtering algorithm for status updates.

Leave a Reply

Your email address will not be published. Required fields are marked *

You may use these HTML tags and attributes: <a href="" title=""> <abbr title=""> <acronym title=""> <b> <blockquote cite=""> <cite> <code> <del datetime=""> <em> <i> <q cite=""> <strike> <strong>