US 6,438,579 B1 · Automated content and collaboration-based system and methods for determining and providing content recommendations

Abstract

A content and collaborative filtering system for recommending entertainment oriented content items, such as music and video, and other media content items to a user based on similarity in profile between the user and other users and between the content indexed in the user's profile and other content in the database. The system stores implicit and explicit ratings data for such content items provided by the users. Upon request of the user, the system accesses the user's profile and corresponding content interests database. The system uses the relationships between the content items to determine a subset of the content items to be referred to the user. The system also correlates a similarity between the user's ratings of the content items and other users' ratings. Based on the correlations, a subset of users is selected that is then used to provide recommendations to the user. The recommended items have a high probability of being subjectively appreciated by the user. The recommendations produced by the system will be represented to the user using a visual representation of the relationships between the content items allowing the user to explore the items related to the recommended items.

Claims22

Dependent claims

A content item referral system, executable by a computer, providing for the automated presentation of a set of recommended media-based content items in response to a query presented by a user, said content item referral system comprising:

a) a weighted relation subsystem operable to provide weighted relationships data representing relative similarities between characteristic attributes of a predetermined set of content items;
b) a referral sub-system, coupled to receive user profile data and said weighted relationship data, responsive to a user query, said referral system operative to perform a traversal of said user profile data and said weighted relationship data to provide an ordered list of content items relative to a predetermined content item;
and
c) an action analysis sub-system coupled to said referral system to receive user action behaviors correlated to content items considered by said user, said action analysis sub-system providing said user profile data to said referral sub-system.

1 more element

A method of providing media content recommendations through a computer server system connected to a network communications system, wherein said computer server system has access to a first database of media content items including media content and related information and a media content filter identifying and providing qualifying attribute relationship data for media content items within said first database, and wherein the media content recommendations are particularly tailored to the personalized interests of a user, said method comprising the steps of:

a) presenting media content items through a network-connected interface to a predetermined user for review and consideration of potential personal interest;
b) monitoring the consideration of said media content items implied through the user directed navigation among the presented media content items and user requests for related information;
c) collecting data from said step of monitoring to develop a user weighted data set reflective of said predetermined user's relative consideration of said media content items;
and
d) evaluating said user weighted data set in combination with said media content filter to identify a set of media content items accessible from said first database for presentation to said predetermined user consistent with said step of presenting.

2 more elements

A content item referral system, executable by a computer, providing for the automated presentation of a set of recommended media content items in response to a query presented by a user, said content item referral system comprising:

a) a first database storing weighted relationships data representing relative similarities between characteristic attributes of a predetermined set of content items;
b) a second database storing user profile data including weighted preferences with respect to a profile respective set of content items;
c) a referral generation system, coupleable to said first database and said second database to access said weighted relationship data and said user profile data, wherein said referral generation system is responsive to a user query to define a graph traversal of said weighted relationship data combined with said user profile data and qualified by a weighted rating and confidence level at predetermined graph traversal steps to provide an ordered list of content items responsive to sold user query and having a predetermined minimum weighted rating and confidence level.

A content item referral system executable by a server computer system coupleable to a communications network and interactively responsive to user actions in connection with the review and selection of media content items through distributed client computer systems, including the sampling of media content items, to provide automated generation of recommended sets of media content items, said content item referral system comprising:

a) an expert database containing attributed expert weighting data defining a first node connected network describing a defined set of content items;
b) a user profile database containing a plurality of user profiles, wherein each said user profile includes attributed personalized weighting data for a respective subset of said defined set of content items, wherein said attributed personalized weighting data is derived from explicit and implicit user actions correlated to said plurality of user profiles, and wherein said attributed personalized weighing data defines a second node connected network;
c) a referral system, coupled to said expert database and said user profile database, responsive to a user query to provide a list of recommended media content items to evaluate a plurality of traversal paths through said first and second node connected networks qualified by a combination of said attributed expert weighting data and said attributed personalized weighting data having at least a determined minimum aggregate weighting, the terminal nodes of said traversal paths representing said list of recommended media content items.

Dependencies are inferred from the claim text.

Automated content and collaboration-based system and methods for determining and providing content recommendations

Life of this patent

Automated content and collaboration-based system and methods for determining and providing content recommendations

Life of this patent

Abstract

Claims22