1. A method comprising: extracting, via a server computing device, user attributes from a static user profile, wherein there are one or more user attributes for each of one or more users in the user profile, said extraction of the user attributes comprising identifying the user attributes on a non-transitory computer-readable storage medium of a computing device hosting the static user profile, and transferring and storing information related to the user attributes in a cache of the server computing device; extracting, via the server computing device, content features from a content profile, wherein there are one or more content features for each of one or more articles in the content profile, and wherein one or more content features are dynamically updated, the content profile being a separately stored profile from the user profile, said extraction of the content features comprising identifying the content features on a non-transitory computer-readable storage medium of a computing device hosting the content profile, and transferring and storing information related to the content features in the cache of the server computing device; creating, via the server comprising device, a new interest model based on variables including the extracted user attributes, the extracted content features, and interest values, wherein there is one interest value associated with each combination of one of the one or more extracted user attributes and one of the one or more extracted content features, said creation of the interest model comprising determined relationships between created equations premised on the variables; optimizing, via the server computing device, the interest model to form an optimized interest model by varying the interest values; searching, via the server computing device, for an article; and returning, via the server computing device in response to said search, a ranking of articles based on the optimized interest model, said return of the ranking comprising analyzing results of said search and performing said ranking by applying said optimized interest model to said results.