Method and system for parsing purchase information from web pages

• US 7,222,090 B2
• Filed: 05/01/2002
• Issued: 05/22/2007
• Est. Priority Date: 08/29/2001
• Status: Active Grant

• Current Assignee: TiVo Corporation (Adeia Inc.)
• Original Assignee: Sedna Patent Services LLC
• Inventors: Oddo, Anthony Scott
• Primary Examiner(s): Rosen; Nicholas D.
• Application Number:
  US10/136,537
• Publication Number:
  US 20030105681A1
• Time in Patent Office: 1,847 Days
• Field of Search: 705/26, 705/27, 707/3, 707/6
• US Class Current: 705/26.62
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0625 Directed, with specific intent or strategy
• CPC Class Codes: Y10S 707/99933 Query processing, i.e. searching
• CPC Class Codes: Y10S 707/99936 Pattern matching access

Abstract

A method for parsing purchase information from code in a Web page. The method includes detecting at least one known product keyword and at least one product data string following that product keyword and being associated with that product keyword. The product data string can be a descriptor for the product keyword for one product in the purchase. The method also includes detecting at least one known transaction keyword and at least one transaction data string following that transaction keyword and being associated with that transaction keyword, the transaction data string being a descriptor for the transaction keyword. The data type of the descriptors can be checked to determine if they are of the same type as the corresponding product or transaction keyword. These processes can be repeated for all of the data strings in the HTML page, and this detected purchase information can be placed into an organized form.

Claims

1. A method for parsing purchase information from code of a Web page for a purchase, comprising:

performing when a sufficient number of product keywords are present to represent a table of product information, the steps of;

parsing the product keywords end placing the product keywords as headings for a table of product information;

parsing and pasting descriptive information for each product in a row under the headings in the table of product information after checking data types to ensure that each descriptor fits with the product keyword;

detecting at least one known transaction keyword and at least one transaction data string following that transaction keyword and being associated with that transaction keyword, the transaction data string being a descriptor for the transaction keyword; and

copying and placing the purchase information into an organized form.

2. The method of claim 1, wherein a first data string that is not a product keyword will be a fitst piece of descriptive information for the product row.

3. The method of claim 1, wherein an end of the row for each product is determined by identifying an indicator in the code.

4. The method of claim 1, wherein the product keywords are product keywords matched from a plurality of product keywords of a common keyword type.

5. The method of claim 4, wherein the keyword types include one or more of a product name, product description, item number, unit price, quantity, and total price.

6. The method of claim 1, wherein the transaction keywords are organized into groups of transaction keywords of common transaction keyword types.

7. The method of claim 6, wherein the common transaction keyword types include one or more of a product total, subtotal, tax, discount, total, shipping type, shipping cost, and credit card type.

8. The method of claim 1, wherein detecting at least one known transaction keyword includes:

performing when a sufficient number of transaction keywords are present to represent a table of transaction information, the steps of;

parsing the transaction keywords and placing the transaction keywords as headings for a table of transaction information; and

parsing descriptive information for each product in a row under the headings in the table of transaction information after checking data types to ensure that each descriptor fits with the transaction keyword.

9. A method for parsing purchase information from code of a Web page for a purchase, comprising:

detecting at least one known product keyword and at least one product data string following hat product keyword and being associated with that product keyword, the product data string being a descriptor for the product keyword for one product in the purchase;

performing when a sufficient number of transaction keywords are present to represent a table of transaction information, the steps of;

parsing the transaction keywords and placing the transaction keywords as headings for a table of transaction information;

parsing descriptive information in a row under the headings in the table of transaction information after checking data types to ensure that each descriptor is an appropriate data type for the transaction keyword; and

copying and placing the purchase information into an organized form.

10. The method of claim 9, wherein the known product keyword is one product keyword matched from a plurality of product keywords of a common keyword type.

11. The method of claim 10, wherein the keyword types include one or more of a product name, product description, item number, unit price, quantity, and total price.

12. The method of claim 9, wherein the transaction keywords are organized into groups of transaction keywords of common transaction keyword types.

13. The method of claim 12, wherein the common transaction keyword types include one or more of a product total, subtotal, tax, discount, total, shipping type, shipping cost, and credit card type.

14. The method of claim 9, further comprising checking each product data string to determine it the product data string is an appropriate data type for the associated product keyword.

15. A method for parsing purchase information from code of a Web page for a purchase, comprising:

locating product information for each product purchased by reviewing data string occurring before a first transaction keyword;

locating product information for each product including;

performing when each data string is pricing information, the steps of;

(a) determinig which type of pricing information is present;

determining a quanity for the product;

(b) determining non-numeric information for the product, the non-numeric information including at least the product name; and

(c) determining an end of the product information for each product;

locating transaction information for the purchase by searching for transaction keywords from the data string; and

copying and placing the located product information and transaction information into an organized form, wherein determining which type of pricing information is present includes;

initially assuming that a first price found is the unit price;

initially assuming that a second price found is the comparative price unless;

the second price equals the first price multiplied by a quantity of the product, in which case the second price is the total price and the first price is the unit price;

or the first price is equal to the second price multiplied by the quantity of the product, in which case the second price is the unit price and the first price is the total price; and

if a third price is found, then the third price is the total price if;

the third price is equal to the second price multiplied by the quantity, in which case the second price is the unit price;

or the third price is equal to tile first price multiplied by the quantity;

in which case the first price is the unit price.

16. A method for parsing purchase information from code of a Web page for a purchase, comprising:

locating product information for each product purchased by reviewing data strings occurring before a first transaction keyword;

locating product information for each product including;

performing when each data string is pricing information, the steps of;

(a) determining which type of pricing information is present;

determining a quantity for the product;

(b) determining non-numeric information for the product, the non-numeric information including at least the product name; and

(c) determining an end of the product information for each product;

locating transaction information for the purchase by searching for transaction keywords from the data strings; and

copying and placing the located product information and transaction information into an organized form, wherein the non-numeric information includes one or more of the product name and product description, and wherein determining non-numeric information for the product includes;

initially assuming that a first non-numeric data string is the product name;

initially assuming that a second non-numeric data string is the product description; and

if a third non-numeric data string is present and if one of the first non-numeric data string and the second non-numeric data string is too short to be informative, replacing the first non-numeric data string or the second non-numeric data string with the third non-numeric string as the product name or product description.