Abstract: A collaborative recommender system which is based on an application of Formal Concept Analysis is disclosed. A problem with collaborative recommender systems based on Formal Concept Analysis is that the size of the concept lattices generated can be very large. Large lattices both take a great deal of time to generate, and tend to include extraneous concepts. In the collaborative recommender systems disclosed herein the size of the concept lattices used are only of a scale required to capture the tastes of an individual user. This reduces the computational resource required by the recommender system markedly. Further improvements are obtained in some embodiments by selecting only relevant concepts from the concept lattice before building a user profile from the selected concepts.

Abstract: A collaborative recommender system which is based on an application of Formal Concept Analysis is disclosed. A problem with collaborative recommender systems based on Formal Concept Analysis is that the size of the concept lattices generated can be very large. Large lattices both take a great deal of time to generate, and tend to include extraneous concepts. In the collaborative recommender systems disclosed herein the size of the concept lattices used are only of a scale required to capture the tastes of an individual user. This reduces the computational resource required by the recommender system markedly. Further improvements are obtained in some embodiments by selecting only relevant concepts from the concept lattice before building a user profile from the selected concepts.