Social Recommender Systems

Abstract

The wealth of information available on the web has made it increasingly difficult to find what one is really looking for. This is particularly true for exploratory queries where one is searching for opinions and views. Think e.g. of the many information channels you can try to find out whether you will love or hate the first Harry Potter movie: you may read the user opinions on Epinions.com or Amazon.com, investigate the Internet Movie Database¹, check the opinion of your favorite reviewers on Rotten Tomatoes¹, read the discussions on a Science Fiction & Fantasy forum², and you can probably add some more possibilities to the list yourself. Although today it has become very easy to look up information, at the same time we experience more and more difficulties coping with this information overload. Hence, it comes as no surprise that personalization applications to guide the search process are gaining tremendous importance. One particular interesting set of applications that address this problem are online recommender sytems [2, 15, 121, 125, 138].

Information networks straddle the world. Nothing remains concealed.

But the sheer volume of information dissolves the information.

We are unable to take it all in.

New Statesman and Society, June 1990. G¨unter Grass