Click through rate prediction using a probabilistic latent variable model

A system comprising:

• One or more server computers connected to the Internet, and
• One or more databases connected to the one or more servers;
• wherein the one or more databases are for storing a matrix of information associated with historical sponsored search activity, the information including user information, query information, and advertisement information associated with the sponsored search activity;
• and wherein the one or more server computers are for:
• modeling the matrix utilizing a probabilistic latent variable model, wherein a latent variable of the model is topical and relates to topics with which users and advertisements can be associated based on the historical sponsored search activity;
• and
• utilizing the model to generate and store a predicted click through rate relating to a first user, a first query and a first advertisement.

A computer readable medium or media containing instructions for executing a method, the method comprising:

• storing, in one or more memories in one or more computers, a matrix of information associated with historical sponsored search activity, the information including user information, query information, and advertisement information associated with the activity;
• using one or more memories of one or more computers, modeling the matrix utilizing a probabilistic latent variable model, wherein a latent variable of the model is topical and relates to topics with which users and advertisements can be associated based on the historical sponsored search activity, comprising:
• approximating the matrix by factorization into a first matrix and a second matrix, wherein:
• the first matrix includes information associating advertisements with topics, wherein the first matrix is kept fixed;
• and
• the second matrix includes information associating users with topics, wherein the second matrix is repeatedly updated based on newly obtained sponsored search activity information;
• using one or more processors of one or more computers, performing matrix multiplication of the first matrix and the second matrix with respect to a first user, a first query and a first advertisement to obtain a first score;
• and
• using one or more processors of one or more computers, generating and storing a predicted click through rate relating to the first user, the first query and the first advertisement by correlating the first score with an associated click through rate.