Report Abstract

This project comprises designing and implementing a hybrid recommender system for web–pages which uses data from a social tagging system to recommend interesting items to users. For this implementation, the tagging data comes from del.icio.us, the oldest and largest public social bookmarking or tagging system for web pages. The system clusters items using a pair of self–organizing maps (SOM) networks and allows users to see the system’s evaluation of their region of interest, or set their own regions.

The focus of this project was the web-scraper for gathering tagged URLs from del.icio.us, and the recommender system. The SOM networks are built using the GHSOM implementation, and several recommenders were built to compare results: one using a single map for URLs and users and the other using separate maps to compare the relative quality of the recommendations.