Recommendation Agents: How to Build an Effective System
Recommendation Agents are an information filtering system that helps identify consumers preferences based on previous purchasing behaviors, or ratings, of a product. Many researchers have looked at different components of the RA systems, but this paper will provide a complete framework of how RA systems work and where they are going in the future. RAs help drive consumer sales through various different algorithms and techniques such as content-based filtering, collaborative-based filtering and co-clustering. RA could take many paths in the future such as looking at each individual click on a computer, personality types, or even moving forward to see how RAs could be used on tablets in stores while consumers are shopping.