Identifying top rated products

The system of claim 3, wherein compute a relevance value for each product in each product category comprises:ncomputing a current rating velocity for each product;computing an average rating velocity for each product; andcomputing the relevance value as a ratio of the average rating velocity and the current rating velocity.

The system of claim 3, wherein compute a relevance value for each product in a product category comprises:ncomputing an average rating velocity for each product;determining an expected number of ratings for each product during a previous time period based on the average rating velocity;determining an amount of time taken for each product to actually receive the expected number of ratings; andcomputing the relevance value for each product as a ratio of the amount of time during the previous time period and the amount of time taken for the product to receive the expected number of ratings.

The system of claim 3, wherein compute a likely next rating score for each of the products in the product category further comprises:ncomputing a prior probability distribution for each product category based upon ratings of the products in the product category;decaying the ratings for each of the products using a time decay factor;modifying the decayed ratings using the relevance value for the product;computing a posterior probability distribution for each product in each category based upon the prior probability distribution for the category and the ratings for each product as decayed by the time decay factor and modified by the relevance value; andcomputing the likely next rating score for each of the products in each product category by computing a predicted next rating for each product in each product category based upon the posterior probability distribution for each product.

The computer-implemented method of claim 10, wherein computing a relevance value for each product in each product category comprises:ncomputing a current rating velocity for each product;computing an average rating velocity for each product; andcomputing the relevance value as a ratio of the average rating velocity and the current rating velocity.

The computer-implemented method of claim 10, wherein computing a relevance value for each product in a product category comprises:ncomputing an average rating velocity for each product;determining an expected number of ratings for each product during a previous time period based on the average rating velocity;determining an amount of time taken for each product to actually receive the expected number of ratings; andcomputing the relevance value for each product as a ratio of the amount of time during the previous time period and the amount of time taken for the product to receive the expected number of ratings.

The computer-implemented method of claim 10, wherein computing a likely next rating score for each of the products in the product category further comprises:ncomputing a prior probability distribution for each product category based upon ratings of the products in the product category;decaying the ratings for each of the products using a time decay factor;modifying the decayed ratings using the relevance value for the product;computing a posterior probability distribution for each product in each category based upon the prior probability distribution for the category and the ratings for each product as decayed by the time decay factor and modified by the relevance value; andcomputing the likely next rating score for each of the products in each product category by computing a predicted next rating for each product in each product category based upon the posterior probability distribution for each product.

The non-transitory computer-readable storage medium of claim 17, wherein compute a relevance value for each product in each product category comprises:ncomputing a current rating velocity for each product;computing an average rating velocity for each product; andcomputing the relevance value as a ratio of the average rating velocity and the current rating velocity.

The non-transitory computer-readable storage medium of claim 17, wherein compute a relevance value for each product in a product category comprises:ncomputing an average rating velocity for each product;determining an expected number of ratings for each product during a previous time period based on the average rating velocity;determining an amount of time taken for each product to actually receive the expected number of ratings; andcomputing the relevance value for each product as a ratio of the amount of time during the previous time period and the amount of time taken for the product to receive the expected number of ratings.

The non-transitory computer-readable storage medium of claim 17, wherein compute a likely next rating score for each of the products in the product category further comprises:ncomputing a prior probability distribution for each product category based upon ratings of the products in the product category;decaying the ratings for each of the products using a time decay factor;modifying the decayed ratings using the relevance value for the product;computing a posterior probability distribution for each product in each category based upon the prior probability distribution for the category and the ratings for each product as decayed by the time decay factor and modified by the relevance value; andcomputing the likely next rating score for each of the products in each product category by computing a predicted next rating for each product in each product category based upon the posterior probability distribution for each product.