1. A method executable by a processor for tailoring information to characteristics of an information user, comprising: passing a request object excluding any profile elements to an input logic using the processor; receiving the request object and accessing a profile database through a profile database proxy using the processor, the profile database containing profile elements that are known to a server but originally excluded from the request object, the profile elements including a user name, network ID, and user interaction history; incorporating the request object with relevant profile elements of the profile elements found in the profile database using the processor; passing the request object with the relevant profile elements to an arbiter using the processor; actively selecting, by analysis of the relevant profile elements using the processor, a personalization engine, which is configured to provide an optimal performance, from a plurality of personalization engines by the arbiter, the arbiter refining and altering a selection based on a number and type of the relevant profile elements, wherein the plurality of personalization engines are a collaborative filtering engine, a predictive-modeling personalization engine, and a business-rules engine, the collaborative filtering engine provides an optimal performance when information is known about a group of users based on statistical knowledge, the predictive-modeling personalization engine provides an optimal performance when a user is unknown based on a short-term usage path of the user, and the business-rules engine provides an optimal performance when the personalization engine needs to change in response to one or more changing circumstances; accessing a content database via a content database proxy to retrieve a personalized content object identified by the personalization engine selected by the arbiter using the processor; and passing with the arbiter the personalized content object to an application program, wherein the arbiter comprises an expert system that is one of rule based, model based, and knowledge based.