Method and system for identifying product-related information on a web page

• US 7,912,755 B2
• Filed: 09/23/2005
• Issued: 03/22/2011
• Est. Priority Date: 09/23/2005
• Status: Expired due to Fees

• Current Assignee: Pronto, Inc. (Match Group, Inc.)
• Original Assignee: Pronto, Inc. (Match Group, Inc.)
• Inventors: Marriott, Daniel Carl, Perry, Nancy Ann, Perry, Bradley John
• Primary Examiner(s): MISIASZEK, MICHAEL
• Assistant Examiner(s): Smith; Jeffrey A
• Application Number:
  US11/234,026
• Publication Number:
  US 20070073758A1
• Time in Patent Office: 2,006 Days
• Field of Search: 705/1, 705/26, 705/27
• US Class Current: 705/26.8
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0633 Lists, e.g. purchase orders, compilation or processing

Abstract

A method and system is provided that in a fully automated manner crawls web sites and identifies specific types of web pages, then extracts targeted data from those web pages. One or more text nodes containing product-related information on a first web page are first identified, and the locations of those text nodes are described using one or more vectors. The vectors are then analyzed to identify one or more patterns and to generate a model from those patterns that discriminates between text nodes that contain product-related information and text nodes that do not contain product-related information on a second web page. The model can then be used to crawl web sites to identify and extract targeted data, or the model can be installed on a user'"'"'s computer to identify and extract targeted information from web sites as the user is browsing.

Claims

1. A method for identifying product-related information on a web page, the method comprising:

identifying one or more text nodes containing product-related information on a first web page;

generating one or more vectors to describe the locations of the text nodes containing product-related information on the first web page;

analyzing one or more of the vectors to identify one or more patterns;

generating, with a server comprising a matcher, a model from the one or more patterns that discriminates between text nodes that contain product-related information and text nodes that do not contain product-related information on a second web page;

transmitting the model to a client application on a users computer; and

using the model to identify and extract product-related information from web pages as the web pages are displayed to the user.

2. The method of claim 1, wherein the first and second web pages are written using HTML programming language.

3. The method of claim 1, wherein the vectors are 4-place vectors.

4. The method of claim 3, wherein one field of the vectors represents the text of the text node.

5. The method of claim 3, wherein one field of the vectors represents the anonymous HTML tag path leading to the text node.

6. The method of claim 3, wherein one field of the vectors represents the indexed HTML tag path leading to the text node.

7. The method of claim 3, wherein one field of the vectors represents the attribute-annotated HTML tag path leading to the text node.

8. The method of claim 1, wherein the model includes one or more symbolic expressions that represent the pattern of text node locations.

9. The method of claim 1, further comprising using the model to crawl a plurality of web pages to identify and extract product-related information.

10. A system for identifying product-related information on a web page, comprising:

a first computer having a first computer-readable storage medium containing;

a copy of source code for a first web page,

one or more first computer programs configured to parse the copy of the source code to identify all text nodes and analyze the text nodes to identify any text nodes that contain product-related information;

one or more second computer programs configured to generate vectors describing the locations of the text nodes containing product-related information, analyze one or more of the vectors to identify one or more patterns and generate one or more models that discriminate between text nodes that contain product-related information and text nodes that do not contain product-related information on a second web page; and

a user computer coupled to the first computer having a second computer-readable storage medium,

wherein the one or more models are transmitted to the second user computer, stored in the second computer-readable medium, and used to identify and extract information about one or more products available for sale on one or more merchant web pages as the web pages are displayed to the user.

11. The system of claim 10, wherein the web pages are written using HTML programming language.

12. The system of claim 10, wherein the vectors are 4-place vectors.

13. The system of claim 12, wherein one field of the vectors represents the text of the text node.

14. The system of claim 12, wherein one field of the vectors represents the anonymous HTML tag path leading to the text node.

15. The system of claim 12, wherein one field of the vectors represents the indexed HTML tag path leading to the text node.

16. The system of claim 12, wherein one field of the vectors represents the attribute-annotated HTML tag path leading to the text node.

17. The system of claim 10, wherein the model includes one or more symbolic expressions that represent the pattern of text node locations.

18. The system of claim 10, wherein the model is used to crawl web pages to identify and extract product-related information.