Automatic recommendation of products using latent semantic indexing of content
First Claim
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.
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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.
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2 Claims
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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.
Specification