Automatic recommendation of products using latent semantic indexing of content

Abstract

Techniques for using latent semantic structure of textual content ascribed to the items to provide automatic recommendations to the user. A user inputs a selected item and, in turn, a latent semantic algorithm is applied to the user selection and the textual content of the items in a database to generate a conceptual similarity between the selection and the items. A set of nearest items to the selected item is provided as a recommendation to the user of other items that may be of particular interest or relevance to the user's original selection based upon the conceptual similarity measure.

What is claimed is  
     
         1 . A method for automatically recommending textual items stored in a database to a user of a computer-implemented service, the method comprising the steps of 
 storing selections of textual items entered by the user,    whenever a new item is added to the database, applying a latent semantic algorithm to the textual items, including the new item, and the stored user selections to establish a conceptual similarity among the textual items, and    alerting the user about the new item whenever the conceptual similarity between the new item and stored selections is within a prescribed value with reference to the conceptual similarity.    
     
     
         2 . The method as recited in  claim 1  wherein the step of alerting includes the step of transmitting electronic mail to the user identifying the new item.