System and method for providing recommendations based on multi-modal user clusters

A computer-readable medium storing instructions for providing document recommendations from a document collection based on multi-modal user clusters, each document in the collection being represented by a first and second feature, the first feature being a text feature, and the second feature being a one of a URL feature, an inlink feature, an outlink feature, an image feature, a user information feature and a text genre feature, the instructions comprising:

• identifying an initial set of users representing a subset of all possible users;
• determining the documents in the collection accessed by the initial set of users;
• for each user of the initial set of users, extrapolating from the documents accessed by the user to the content of the documents accessed by the user;
• clustering the initial set of users into a plurality of user clusters by representing each user of the initial set using the content of the documents accessed by the user;
• identifying a new user;
• collecting information about documents accessed by the new user;
• and
• assigning the new user to a user cluster based upon similarity between documents accessed by the new user and the content of the documents accessed by other users included in the user cluster.

A signal representing instructions for providing page recommendations from a page collection based on multi-modal user clusters, each page in the collection being represented by a first and a second feature vector, each of the first and second feature vectors being a multi-dimensional vector, the first feature vector being representative of a first feature of the pages and the second feature vector being representative of a second feature of the pages, the first feature being a text feature, and the second feature being a one of a set of multi-modal features including a URL feature, an inlink feature, an outlink feature an image feature, a user information feature and a text genre feature, the instructions comprising:

• identifying an initial set of users representing a subset of all possible users;
• determining the pages in the collection accessed by each of the initial set of users;
• for each user of the initial set of user, extrapolating from the pages accessed by the user to the content of the pages accessed by the user;
• clustering the initial set of users into a plurality of user clusters by representing each user of the initial set using the content of the pages accessed by the user;
• identifying a new user;
• collecting information about page accesses by the new user;
• and
• assigning the new user to a user cluster based upon similarity between pages accessed by the new user and the user cluster and the content of the pages accessed by other user included in the user cluster.