A Taxonomy of Recommender Agents on theInternet
Artificial Intelligence Review
IEEE Transactions on Knowledge and Data Engineering
Introduction to recommender systems
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
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The area of Recommendation Systems (RS) is a fairly fragmented but rapidly developing field, widely researched, young but mature. Nonetheless, given the complexity of designing any type of RS, it is helpful to create tools that can serve as building blocks by identifying the different possibilities on the way to properly select the recommendation techniques that fit best with system requirements. This paper wishes to clearly define and organize these fundamental choices bearing in mind the order in which they should be taken. With this purpose and based on a literature review of overall concepts from the area of RS, a list was created of key design decisions that need to be made when building any type of RS solution that can in addition consider adaptation/personalization criteria. Hence, the proposed list serves as a guide for any developer that wishes to create her/his own RS.