Aggregation of emailed product order and shipping information

• US 9,641,474 B2
• Filed: 08/12/2014
• Issued: 05/02/2017
• Est. Priority Date: 07/19/2011
• Status: Active Grant

• Current Assignee: Nielsen Consumer LLC (Nielsen Holdings plc)
• Original Assignee: Slice Technologies, Inc. (Rakuten Group, Inc.)
• Inventors: Brady, Scott J., Suppe, Benjamin A., Mastierov, Ievgen, Khosla, Aditya, Mykhaylov, Dmytry B., Verbytskyi, Georgii, Botto, Eric J., Madan, Harpinder Singh
• Primary Examiner(s): Desrosiers, Evans
• Application Number:
  US14/457,421
• Publication Number:
  US 20140358814A1
• Time in Patent Office: 994 Days
• Field of Search: 726 1- 7, 713155-159, 709 22
• CPC Class Codes: G06F 21/31 User authentication
• CPC Class Codes: G06Q 10/08 Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
• CPC Class Codes: G06Q 10/107 Computer-aided management of electronic mailing [e-mailing]
• CPC Class Codes: G06Q 30/00 Commerce
• CPC Class Codes: G06Q 30/0601 Electronic shopping [e-shopping]
• CPC Class Codes: H04L 51/00 User-to-user messaging in packet-switching networks, transmitted according to store-and-forward or real-time protocols, e.g. e-mail
• CPC Class Codes: H04L 51/42 Mailbox-related aspects, e.g. synchronisation of mailboxes

Abstract

Product order and shipping information received via email messages is automatically aggregated for ready user review. Once the user is authenticated, authorization to access their email mailbox is obtained and the email message headers of their emails are analyzed to identify those messages of interest. The bodies of the email messages of interest are parsed to extract the product order and shipping information which is stored and presented for display to the user typically grouped by individual product thus greatly simplifying user review of orders.

Claims

1. A method performed by computer apparatus, the method comprising:

for each of multiple merchants, determining at least one respective template that defines a respective grammar that describes a respective language and a respective format of a purchase-related electronic message body;

converting, by a processor, each template into a respective extraction parser that is associated with the respective merchant based on the respective grammar, wherein the converting comprises, for each template, deriving a respective context-free grammar based on the respective grammar defined in the template and generating the respective extraction parser based on the respective derived context-free grammar;

identifying purchase-related electronic messages transmitted between network nodes and stored in a first non-transitory networked data storage location;

for each of respective ones of the identified purchase-related electronic messages associated with respective ones of the merchants,

selecting, by a processor, the extraction parser associated with the respective merchant, and

applying, by a processor, the selected extraction parser to unstructured free form text in a body portion of a selected one of the identified purchase-related electronic messages to extract purchase-related information corresponding to a set of purchase-related data fields from the unstructured free form text, wherein the body portion of the selected one of the identified purchase-related electronic messages lacks structured tag elements that delineate the purchase-related fields in the set;

storing the extracted purchase-related information as aggregated data in a second non-transitory networked data storage location; and

in response to a request from a client network node associated with a user, transmitting data for displaying a view on the aggregated data on the client network node.

2. The method of claim 1, wherein the selecting comprises choosing the respective extraction parser based on identification of a sender of the purchase-related electronic message from a predefined set of merchants.

3. The method of claim 2, wherein the choosing of the respective extraction parser is further based on identification of a type of the purchase-related electronic message selected from a predefined set of electronic message types.

4. The method of claim 3, wherein the predefined set of electronic message types comprises an order confirmation message type and a shipping confirmation message type.

5. The method of claim 3, wherein the choosing of the respective extraction parser is further based on identification of a format of a body portion of the electronic message selected from a predefined set of electronic message body formats.

6. The method of claim 1, wherein for each of respective ones of the templates, the respective defined grammar describes a respective format of purchase-related fields in a body portion of an electronic message.

7. The method of claim 6, wherein the grammar of a respective one of the templates describes a format of a set of purchase-related fields comprising a greeting field, an order details field, a purchase item details field, and a tax and totals field.

8. The method of claim 1, further comprising, based on the applying of the selected extraction parser to the body portion of the electronic message, extracting purchase-related information comprising one or more of an order number, a product description, a product name, a product price, and an order total.

9. The method of claim 1, further comprising, based on the applying of the selected extraction parser to the body portion of the electronic message, extracting purchase-related information comprising one or more of a tracking number, a shipping address, a billing address, an estimated shipping date, and an estimated delivery date.

10. The method of claim 1, wherein the storing comprises creating a respective database record for each of multiple product orders and aggregating the purchase-related information extracted from ones of the electronic messages relating to each product order in the respective database record.

11. The method of claim 1, wherein the transmitting comprises transmitting extracted purchase-related information to a network node to generate a view on the extracted purchase-related information grouped by individual ordered product.

12. The method of claim 11, wherein the view on the aggregated data comprises a product order date, a product description, a product price, a product merchant, and a product order status for each individual ordered product.

13. The method of claim 1, wherein the electronic messages are electronic mail messages.

14. The method of claim 1, wherein each respective derived context-free grammar is formatted in a Backus-Naur Form.

15. The method of claim 1, wherein, for each of the templates, the deriving comprises applying a parser generator to the respective grammar defined in the template to produce the respective context-free grammar.

16. The method of claim 15, wherein, for each of the templates, the generating comprises applying a parser generator to the respective derived context-free grammar to produce the respective extraction parser.

17. A system, comprising

a non-transitory memory storing processor-readable instructions, and

a processor coupled to the non-transitory memory, operable to execute the instructions, and based at least in part on the execution of the instructions operable to perform operations comprising:

for each of multiple merchants, determining at least one respective template that defines a respective grammar that describes a respective language and a respective format of a purchase-related electronic message body;

converting, by a processor, each template into a respective extraction parser that is associated with the respective merchant based on the respective grammar, wherein the converting comprises, for each template, deriving a respective context-free grammar based on the respective grammar defined in the template and generating the respective extraction parser based on the respective derived context-free grammar;

identifying purchase-related electronic messages transmitted between network nodes and stored in a first non-transitory networked data storage location;

for each of respective ones of the identified purchase-related electronic messages associated with respective ones of the merchants,

selecting, by a processor, the extraction parser associated with the respective merchant, and

applying, by a processor, the selected extraction parser to unstructured free form text in a body portion of a selected one of the identified purchase-related electronic messages to extract purchase-related information corresponding to a set of purchase-related data fields from the unstructured free form text, wherein the body portion of the selected one of the identified purchase-related electronic messages lacks structured tag elements that delineate the purchase-related fields in the set;

storing the extracted purchase-related information as aggregated data in a second non-transitory networked data storage location; and

in response to a request from a client network node associated with a user, transmitting data for displaying a view on the aggregated data on the client network node.

18. At least one non-transitory computer readable medium comprising instructions, which when executed by computer apparatus, cause the computer apparatus to perform operations comprising:

for each of multiple merchants, determining at least one respective template that defines a respective grammar that describes a respective language and a respective format of a purchase-related electronic message body;

converting, by a processor, each template into a respective extraction parser that is associated with the respective merchant based on the respective grammar, wherein the converting comprises, for each template, deriving a respective context-free grammar based on the respective grammar defined in the template and generating the respective extraction parser based on the respective derived context-free grammar;

identifying purchase-related electronic messages transmitted between network nodes and stored in a first non-transitory networked data storage location;

for each of respective ones of the identified purchase-related electronic messages associated with respective ones of the merchants,

selecting, by a processor, the extraction parser associated with the respective merchant, and

applying, by a processor, the selected extraction parser to unstructured free form text in a body portion of a selected one of the identified purchase-related electronic messages to extract purchase-related information corresponding to a set of purchase-related data fields from the unstructured free form text, wherein the body portion of the selected one of the identified purchase-related electronic messages lacks structured tag elements that delineate the purchase-related fields in the set;

storing the extracted purchase-related information as aggregated data in a second non-transitory networked data storage location; and

in response to a request from a client network node associated with a user, transmitting data for displaying a view on the aggregated data on the client network node.