Method and system for mining websites

• US 9,230,030 B2
• Filed: 12/22/2008
• Issued: 01/05/2016
• Est. Priority Date: 12/22/2008
• Status: Active Grant

• Current Assignee: NBC Universal Media LLC (Comcast Corporation)
• Original Assignee: NBC Universal Media LLC (Comcast Corporation)
• Inventors: Xue, Feng, Moitra, Abha, Gustafson, Steven Matt
• Primary Examiner(s): Coulter, Kenneth R
• Application Number:
  US12/340,935
• Publication Number:
  US 20100161785A1
• Time in Patent Office: 2,570 Days
• Field of Search: 709/224, 709/227, 709/228, 707/776, 707/769, 706/12, 706/45
• US Class Current: 1/1
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: H04L 67/535 Tracking the activity of the user network monitoring arrangements H04L43/00; recording of computer activity G06F11/34

Abstract

One website mining embodiment is for characterizing first time users of a website, collecting user session data of the users visiting the website and identifying first time visitors, determining features of the first time visitors utilizing the user session data, determining rules utilizing the features of the first time visitors, monitoring actions of the first time visitors on the website, updating the rules utilizing the monitored actions of the first time visitors and recommending web content utilizing the rules to the first time visitor.

Claims

1. A computer hardware implemented method of website mining, comprising:

collecting user session data of users visiting the website and identifying first time visitors;

determining features of the first time visitors utilizing the user session data;

determining rules utilizing the features of the first time visitors;

providing recommendations of web content comprising a webpage by applying the rules;

monitoring actions of the first time visitors on the website, wherein the monitoring of actions of the first time visitors include acceptance of the recommendations, rejection of the recommendations, time spent to review recommended data, time spent on the website after recommendations, or a combination thereof; and

updating the rules utilizing the monitored actions of the first time visitors.

2. The method of claim 1 wherein the first time visitors are tagged for identification of the first time visitors.

3. The method of claim 1, wherein identifying the first time visitors comprises identifying users that have not visited the website for a predefined time period, has downloaded data less than a predetermined size from the website, or both.

4. The method of claim 1, wherein the features of the first time visitors include date of visit, time of visit, client IP address, user name, service name, client server name, client server IP address, server port, method, protocol status, Win32 status, bytes sent, bytes received, protocol version, host, user agent, cookie, referrer, website pages viewed, operating system, city of the first time visitor, country of the first time visitor and session id.

5. The method of claim 1, wherein the features of the first time visitors are stored in a hash table.

6. The method of claim 1, wherein the features of the first time visitor are stored in a logfile database.

7. The method of claim 1, wherein the rules of the first time visitors are derived using Classification and Regression Trees.

8. The method of claim 1, wherein the determination and updating the rules is done offline.

9. The method of claim 1, comprising:

recommending the web content on the basis of the rules corresponding to the features of the first time visitor.

10. The method of claim 1, wherein the recommendation of web content to the first time visitor is done online.

11. The method of claim 1, wherein the recommendations are made utilizing highly ranked rules in the rules database.

12. The method of claim 1, wherein the rules determined have a ranking of preference.

13. The method of claim 1, wherein updating the rules include updating rankings of the existing rules based upon the actions.

14. The method of claim 1, wherein updating the rules include comparing a determined rule with an existing rule.

15. The method of claim 14 wherein the determined rule is stored in the database if the determined rule does not exist in the existing rules.

16. The method of claim 1, wherein the monitoring of actions of the first time visitors comprises at least two of acceptance of the recommendations, rejection of the recommendations, time spent to review recommended data, and time spent on the website after recommendations.

17. The method of claim 1, comprising:

retaining the recommendations for subsequent first time visitors when the first time visitors accept the recommendations; and

discarding the recommendations for the subsequent first time visitors when the first time visitors reject the recommendations.

18. A system of website mining comprising:

a webserver for storing web usage data of a website in a non-transitory storage device; and

a webserver engine connected to the webserver for;

processing the user session data to determine features of first time visitors of the website and determining rules based on the features of the first time users;

providing recommendations of web content comprising a webpage by applying the rules;

monitoring actions of the first time visitor to update the rules, wherein the monitoring of actions of the first time visitors include acceptance of the recommendations, rejection of the recommendations, time spent to review recommended data, time spent on the website after recommendations, or a combination thereof; and

updating the rules based on the actions of the first time visitors.

19. The system of claim 18 wherein the website has a finite number of hierarchical levels with mapping from each website page into the hierarchical levels, and

wherein each user session is mapped to the hierarchical levels of the website.

20. A computer hardware implemented method of website mining, comprising:

collecting user session data of users visiting the website and identifying first time visitors;

determining features of the first time visitors utilizing the user session data;

determining ranked rules utilizing the features of the first time visitors;

monitoring actions of the first time visitors on the website, wherein the monitoring of actions of the first time visitors comprises acceptance of the recommendations, rejection of the recommendations, time spent to review recommended data, and time spent on the website after recommendations; and

updating the ranked rules utilizing the monitored actions of the first time visitors.