System and method for analyzing internet usage

• US 8,204,928 B2
• Filed: 10/10/2008
• Issued: 06/19/2012
• Est. Priority Date: 10/10/2008
• Status: Active Grant

• Current Assignee: Caterpillar Incorporated
• Original Assignee: Caterpillar Incorporated
• Inventors: Elven, Darrell Ray
• Primary Examiner(s): Fan, Hua
• Application Number:
  US12/285,682
• Publication Number:
  US 20100095215A1
• Time in Patent Office: 1,348 Days
• Field of Search: 709/200
• US Class Current: 709/200
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: H04L 67/02 based on web technology, e.g. hypertext transfer protocol [HTTP]
• CPC Class Codes: H04L 67/535 Tracking the activity of the user network monitoring arrangements H04L43/00; recording of computer activity G06F11/34
• CPC Class Codes: H04L 67/564 Enhancement of application control based on intercepted application data
• CPC Class Codes: H04L 69/28 Timers or timing mechanisms used in protocols

Abstract

A computer-implemented method for detecting a repetitive activity pattern is disclosed. The method may include receiving activity data. The activity data may include timing information of a plurality of events. The method may also include determining a series of interval times associated with the plurality of events. The method may further include calculating a series of single standard deviations representing a running standard deviation of the series of interval times. The method may also include calculating a double standard deviation of the series of single standard deviations. The method may yet further include detecting a repetitive activity pattern if the double standard deviation is below a first pre-determined standard deviation threshold for a time period longer than a time threshold.

Claims

1. A computer-implemented method for analyzing Internet usage, the method comprising:

receiving proxy log data, wherein the proxy log data include timing information of a plurality of Internet events;

determining a series of interval times associated with the plurality of Internet events;

calculating, using at least one hardware processor, a series of single standard deviations representing a running standard deviation of the series of interval times;

calculating a double standard deviation of the series of single standard deviations; and

detecting, using at least one hardware processor, an automated activity if the double standard deviation is below a first pre-determined standard deviation threshold for a time period longer than a time threshold.

2. The method of claim 1, further including detecting an automated activity if a single standard deviation is below a second pre-determined standard deviation threshold for a time period longer than the time threshold.

3. The method of claim 1, wherein determining a series of interval times includes:

sorting the proxy log data in a chronological order; and

determining each interval time as a temporal distance between every two consecutive proxy log data.

4. The method of claim 1, wherein the automated activity is an automated webpage refresh.

5. The method of claim 1, wherein the automated activity is an automated webpage pop-out.

6. The method of claim 1, further including indicating the detected automated activity to a user via a display interface.

7. The method of claim 6, further including:

receiving an input from the user, wherein the input includes a permission to remove the automated activity; and

removing proxy log data that correspond to the automated activity from a proxy log.

8. The method of claim 1, further including determining an active Internet usage time by excluding a duration of the automated activity from a total Internet usage time.

9. An Internet usage analyzer, comprising:

a network interface configured to receive proxy log data from a proxy server, the proxy log data include timing information of a plurality of Internet events; and

a hardware processor coupled to the network interface and configured to;

determine a series of interval times associated with the plurality of Internet events;

calculate a series of single standard deviations representing a running standard deviation of the series of interval times;

calculate a double standard deviation of the series of single standard deviations; and

detect an automated activity if the double standard deviation is below a first pre-determined standard deviation threshold for a time period longer than a time threshold.

10. The Internet usage analyzer of claim 9, wherein the hardware processor is further configured to detect an automated activity if a single standard deviation is below a second pre-determined standard deviation threshold for a time period longer than the time threshold.

11. The Internet usage analyzer of claim 9, wherein the hardware processor being configured to determine a series of interval times includes the hardware processor being configured to:

sort the proxy log data in a chronological order; and

determine each interval time as a temporal distance between every two consecutive proxy log data.

12. The Internet usage analyzer of claim 9, further including a display interface configured to indicate the detected automated activity to a user of the Internet usage analyzer.

13. The Internet usage analyzer of claim 12, further including an input and output interface configured to receive an input from the user, wherein the input includes a permission to remove the automated activity;

and the hardware processor is further configured to remove proxy log data that correspond to the automated activity from a proxy log.

14. The Internet usage analyzer of claim 9, wherein the hardware processor is further configured to determine an active Internet usage time by excluding a duration of the automated activity from a total Internet usage time.

15. A non-transitory computer-readable storage medium storing instructions that, when executed by a computer including at least one processor, cause the computer to perform a method for analyzing Internet usage, the method comprising:

receiving proxy log data, wherein the proxy log data include timing information of a plurality of Internet events;

determining a series of interval times associated with the plurality of Internet events;

calculating a series of single standard deviations representing a running standard deviation of the series of interval times;

calculating a double standard deviation of the series of single standard deviations; and

detecting an automated activity if the double standard deviation is below a first pre-determined standard deviation threshold for a time period longer than a time threshold.

16. The non-transitory computer-readable storage medium of claim 15, the method further including detecting an automated activity if a single standard deviation is below a second pre-determined standard deviation threshold for a time period longer than the time threshold.

17. The non-transitory computer-readable storage medium of claim 15, wherein determining a series of interval times includes:

sorting the proxy log data in a chronological order; and

determining each interval time as a temporal distance between every two consecutive proxy log data.

18. The non-transitory computer-readable storage medium of claim 15, wherein the automated activity is an automated webpage refresh.

19. The non-transitory computer-readable storage medium of claim 15, wherein the automated activity is an automated webpage pop-out.

20. The non-transitory computer-readable storage medium of claim 15, the method further including indicating the detected automated activity to a user via a display interface.