System and method for influencing recommender system & advertising based on programmed policies

A method of presenting advertising via an electronic device in conjunction with recommendations made by a recommender system, comprising:

• defining a pay-for-placement influence policy applicable to a third party advertiser;
• implementing a biasing policy based on the influence policy for influencing recommendations made by the recommender system to a user of the recommender system,
• wherein said biasing policy is representative of preferences of the third party advertiser, and biases the recommender system to recommend items associated with the third party advertiser;
• responding to a request for a recommendation;
• and
• presenting advertising content based on the biasing policy while presenting policy influenced recommendation to the user in response to the request.

A recommender system operating on a website and programmed to provide recommendations to users for items in response to a request for a recommendation, comprising:

• a first software routine for defining a pay-for-placement influence policy applicable to a third party advertiser;
• a second software routine for establishing a biasing policy based on the influence policy for influencing recommendations made by the recommender system to a user of the recommender system,
• wherein the biasing policy is representative of preferences of the third party advertiser, and biases the recommender system to recommend items associated with the third party advertiser, and
• wherein the recommender system applies the biasing policy to present policy influenced recommendations to the user in response to the request for a recommendation.

A method of recommending items of interest to a user of an online service provider, comprising:

• maintaining a profile for a user at the online service provider, wherein the profile includes prior selections and/or ratings of items made by the user;
• providing one or more recommendations to the user using a recommender system which uses account profiles of users similar to the user to generate such recommendations;
• defining a pay-for-placement influence policy applicable to a third party advertiser;
• defining a first item which is to receive a preference from the recommender system based on the influence policy,
• wherein the preference biases the recommender system to recommend items associated with the third party advertiser;
• and
• selectively influencing the recommender system on a subscriber by subscriber basis, so that the first item is presented to a user in a policy influenced recommendation based on the preference when the user's profile meets criteria of the influence policy,
• wherein the influence policy can be used to present recommendations of items to the user which would not otherwise be presented by the recommender system to the user.

A method of recommending items of interest to a user of an online service provider, comprising:

• maintaining a profile for a user at the online service provider, wherein the profile includes prior selections and/or ratings of items made by the user;
• providing recommendations in a first list to the user over an electronic communications network using a recommender system which uses account profiles of other users similar to the user to generate such recommendations;
• defining a pay-for-placement influence policy applicable to a third party advertiser;
• defining a first item which is to be recommended by the recommender system based on the influence policy and preference factors unrelated to the account profiles of other users,
• wherein the preference factors bias the recommender system to recommend items associated with the third party advertiser;
• and
• selectively influencing the recommender system such that the first item is presented, based on the influence policy and the preference factors, only to selected users residing within predefined geographic regions,
• wherein the influence policy can be used to present recommendations of items to the user which would not otherwise be presented by the recommender system over the electronic communications network to the user in the first list.

A method of recommending items of interest to users of an online service provider, comprising:

• defining a pay-for-placement influence policy applicable to a third party advertiser;
• providing an influenced recommendation based on a biasing policy derived from the influence policy for a first item to a user over a network using a collaborative filtering based recommendation engine,
• wherein the biasing policy is representative of preferences of the third party advertiser, and biases the recommender system to recommend items associated with the third party advertiser, and
• wherein the first item is characterized by a first content associated with a first identifiable source of content;
• and
• providing an advertisement to the user which is correlated to the influenced recommendation, the advertisement being generated by an advertising delivery system and describing a second item to the user over the network,
• wherein the second item is characterized by a second content that is also associated with the first identifiable source of content, and
• wherein presentation of recommendations and advertisements are coordinated for users the user of the online service provider.

A method of recommending items of interest to users of an online service provider, comprising:

• defining a pay-for-placement influence policy applicable to a third party advertiser;
• providing an influenced recommendation based a biasing policy derived from the influence policy for a first item to a user over a network using a collaborative filtering based recommendation engine,
• wherein the biasing policy is representative of preferences of the third party advertiser, and biases the recommender system to recommend items associated with the third party advertiser;
• and
• providing an advertisement to the user which is correlated to the recommendation, the advertisement being generated by an advertising delivery system and describing a second item to the user over the network,
• wherein the second item is related logically to the first item and is associated with a context presented the user in which the first item is presented,
• wherein presentation of recommendations and advertisements are coordinated for the user of the online service provider.

A recommender system for recommending items of interest to users interacting with an online service provider, comprising:

• means for defining a pay-for-placement influence policy applicable to a third party advertiser;
• means for providing a biasing policy based on the influence policy to influence recommendations made by the recommendation system,
• wherein the biasing policy is representative of preferences of the third party advertiser, and biases the recommender system to recommend items associated with the third party advertiser;
• means for responding to a request for a recommendation from a user;
• and
• means for implementing the biasing policy when presenting recommendations to the user in response to the request.

A computer-readable medium having stored thereon, computer-executable instructions that, if executed by a computing device, cause the computing device to perform a method comprising:

• defining a pay-for-placement influence policy applicable to a third party advertiser;
• establishing a biasing policy based on the influence policy for influencing recommendations made by the recommender system to a user of the recommender system,
• wherein the biasing policy is representative of preferences of the third party advertiser, and biases the recommender system to recommend items associated with the third party advertiser;
• responding to a request for a recommendation;
• and
• applying the biasing policy to the recommender system when presenting a policy influenced recommendation in response to the request.

A method for influencing a recommender system, comprising:

• defining a pay-for-placement influence policy applicable to a third party advertiser;
• specifying third party advertiser preferences from the influence policy;
• implementing the third party advertiser preferences to bias the recommender system to items associated with the third party advertiser;
• responding to a recommendation request from a user;
• generating a policy influenced recommendation for the user by enforcing the influence policy;
• presenting the policy influenced recommendation to the user;
• and
• evaluating performance of the influence policy.