About Recommender Systems

About Recommender Systems

Recommender systems are software applications that aim to support users in their decision-making while interacting with large information spaces. They recommend items of interest to users based on preferences they have expressed, either explicitly or implicitly. The ever-expanding volume and increasing complexity of information on the Web has therefore made such systems essential tools for users in a variety of information seeking or e-commerce activities. Recommender systems help overcome the information overload problem by exposing users to the most interesting items, and by offering novelty, surprise, and relevance. Recommender technology is hence the central piece of the information seeking puzzle. Major e-commerce sites such as Amazon and Yahoo are using recommendation technology in ubiquitous ways. Many new comers are on their way and entrepreneurs are competing in order to find the right approach to use this technology effectively.

Some say that recommendation technology represents the new paradigm of search: interesting items find the user instead of the user explicitly searching for them. In an article published in CNN Money, entitled “The race to create a 'smart' Google”, Fortune magazine writer Jeffrey M. O'Brien, writes:

 

 

The Web, they say, is leaving the era of search and entering one of discovery. What's the difference? Search is what you do when you're looking for something. Discovery is when something wonderful that you didn't know existed, or didn't know how to ask for, finds you.