Method and apparatus for tailoring content of information delivered over the internet

Apparatus for tailoring information in a combination of hardware and software to characteristics of an information user, the apparatus comprising:

• a content database;
• an input logic for receiving a request object excluding any profile elements and accessing a profile database through a profile database proxy, the profile database containing profile elements that are known to a server but originally excluded from the request object, the input logic configured to incorporate into the request object any relevant profile elements of the profile elements found in the profile database including a user name, network ID, and user interaction history;
• an arbiter for accepting and analyzing a request object having the relevant profile elements, which is passed by the input logic, the arbiter refining and altering a selection based on a number and type of at least one of the profile elements contained in the request object;
• a plurality of personalization engines for selecting at least one personalized content object from the content database, 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;
• the arbiter selecting a personalization engine from the plurality of personalization engines, and the selected personalization engine selects the at least one personalization content object from the content database via a content database proxy;
• and
• the arbiter passing 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.

A method executable by a processor for tailoring information delivered to a 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;
• selecting with the arbiter a personalization engine by analysis of the relevant profile elements, wherein the personalization engine is at least one of 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;
• selecting with the personalization engine a personalized content object to tailor information provided to the user, wherein the personalized content object is stored in a content database and accessed via a content database proxy;
• and
• using the arbiter for on-line shopping,
• wherein the arbiter comprises an expert system that is one of rule based, model based, and knowledge based.