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Purchase confirmation data extraction with missing data replacement

  • US 10,055,718 B2
  • Filed: 09/27/2016
  • Issued: 08/21/2018
  • Est. Priority Date: 01/12/2012
  • Status: Active Grant
First Claim
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1. A method implemented by one or more computing devices specifically programmed to perform operations comprising:

  • automatically, by one or more of the computing devices, parsing purchase confirmation messages corresponding to respective purchase transactions to extract sets of structured text strings for respective target purchase-related field types comprising a product description field type and one or more price field types;

    for each of one or more of the extracted sets of structured text strings corresponding to a respective multi-product purchase transaction and comprising a respective partial description text string for a first one of the products and one or more total price text strings for the respective purchase transaction but missing an individual price text string for the first product, by one or more of the computing devices,building a respective query as a function of the partial description text string for the first product,determining respective upper and lower price bounds for the first product as a function of one or more of the total price text strings for the respective purchase transaction,sending at least one request comprising the query to at least one network address that triggers at least one server network node to execute a search engine to return at least one electronic document comprising a respective dynamically generated ranked list of product-related items matching the query and comprising respective sets of descriptions and individual prices for respective products, wherein the product-related items in the list are unconnected to the respective purchase transaction and are derived from at least one of (i) records of purchase transactions other than the respective purchase transaction and (ii) records of products offered for purchase,selecting a product-related item in the ranked list of product-related items by evaluating one or more of the individual product prices in one or more of the product-related items against the respective upper and lower price bounds for the first product and one or more heuristics that preferentially select higher ranked product-related items over lower ranked product-related items,excerpting a respective complete product description text string and a respective individual product price text string from the selected product-related item, andaugmenting the extracted set of structured text strings for the respective purchase transaction with the excerpted complete product description text string and the respective individual product price text string; and

    aggregating, by one or more of the computing devices, the extracted and augmented sets of structured text strings to produce actionable data for visualizing purchase graph information.

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