METHOD AND SYSTEM FOR PREDICTIVE BROWSING

• US 20090210806A1
• Filed: 02/20/2008
• Published: 08/20/2009
• Est. Priority Date: 02/20/2008
• Status: Active Grant

• Current Assignee: Kyndryl Incorporated
• Original Assignee: International Business Machines Corporation
• Inventors: Dodson, Christopher N., Locke, Richard A., O'Connell, Brian M., Walker, Keith R.
• Granted Patent: US 8,560,964 B2
• Time in Patent Office: Days
• US Class Current: 715/760
• CPC Class Codes: G06F 16/957 Browsing optimisation, e.g. caching or content distillation
• CPC Class Codes: G06F 3/0484 for the control of specific functions or operations, e.g. selecting or manipulating an object, an image or a displayed text element, setting a parameter value or selecting a range

Abstract

A method for automatically navigating potential websites for predictive browsing based on user activities along with efficiency of verifying content updates. A Uniform Resource Locator (URL) of websites and its associated attributes that a user visits can be recorded and stored in a storage engine. The potential sites can be predicted by a predictive engine component based upon a past browsing history and various environmental factors that are recorded in the storage engine. A dynamic content detection engine component examines each potential websites and detects if the site has been updated. The predictive engine enables the user to navigate to the potential websites thereby permitting the user to browse websites faster.

Claims

1. A computer implemented method for predictive browsing, comprising:

automatically recording and updating an URL and a plurality of attributes associated with a website in response to activation of said website by at least one user and storing said URL and said plurality of attributes in a storage engine;

predicting at least one potential site of interest to said at least one user based upon a past browsing history and said plurality of attributes associated with said storage engine by a predictive engine component; and

invoking a dynamic content detection component for verifying content updates corresponding to said at least one potential site and automatically prompting said at least one user to select said at least one potential site utilizing a website selection control thereby permitting said at least one user to browse websites faster.

2. The computer implemented method of claim 1 further comprising;

prompting said at least one user to select said at least one potential site as a user preference; and

storing said user preference in a preference table.

3. The computer implemented method of claim 1 wherein said dynamic content detection component comprises header based detection, content comparison, non-essential change detection and user selectable content section in order to detect said content updates.

4. The computer implemented method of claim 1 wherein said plurality of attributes comprises day-of-week, time-of-day, number of visits and a previous website associated with said website.

5. The computer implemented method of claim 1 wherein said website selection control comprises a standard web browser program with a browser plug-in.

6. The computer implemented method of claim 1 wherein said website selection control comprises a plurality of graphically displayed buttons, such that each graphically displayed button among said plurality of graphically displayed buttons corresponds to a different list of web sites based on said at least one user activity.

7. The computer-implemented method of claim 1 wherein said storage engine comprises a learning component in order to rank said at least one potential website based on said at least one user activity.

8. A system, comprising:

a processor;

a data bus coupled to said processor; and

a computer-usable medium embodying computer code, said computer-usable medium being coupled to said data bus, said computer program code comprising instructions executable by said processor and configured for;

automatically recording and updating an URL and a plurality of attributes associated with a website in response to activation of said website by at least one user and storing said URL and said plurality of attributes in a storage engine;

predicting at least one potential site of interest to said at least one user based upon a past browsing history and said plurality of attributes associated with said storage engine by a predictive engine component; and

invoking a dynamic content detection component for verifying content updates corresponding to said at least one potential site and automatically prompting said at least one user to select said at least one potential site utilizing a website selection control thereby permitting said at least one user to browse websites faster.

9. The system of claim 8, wherein said instructions are further configured for:

prompting said at least one user to select said at least one potential site as a user preference; and

storing said user preference in a preference table.

10. The system of claim 8, wherein said dynamic content detection component comprises header based detection, content comparison, non-essential change detection and user selectable content section in order to detect said content updates.

11. The system of claim 8, wherein said plurality of attributes comprises day-of-week, time-of-day, number of visits and a previous website associated with said website.

12. The system of claim 8, wherein said website selection control comprises a standard web browser program with a browser plug-in.

13. The system of claim 8, wherein said website selection control comprises a plurality of graphically displayed buttons, such that each graphically displayed button among said plurality of graphically displayed buttons corresponds to a different list of web sites based on said at least one user activity.

14. The system of claim 8, wherein said storage engine comprises a learning component in order to rank said at least one potential website based on said at least one user activity.

15. A computer-usable medium embodying computer program code, said computer program code comprising computer executable instructions configured for:

automatically recording and updating an URL and a plurality of attributes associated with a website in response to activation of said website by at least one user and storing said URL and said plurality of attributes in a storage engine;

predicting at least one potential site of interest to said at least one user based upon a past browsing history and said plurality of attributes associated with said storage engine by a predictive engine component; and

invoking a dynamic content detection component for verifying content updates corresponding to said at least one potential site and automatically prompting said at least one user to select said at least one potential site utilizing a website selection control thereby permitting said at least one user to browse websites faster.

16. The computer-usable medium of claim 15, wherein said embodied computer program code further comprises computer executable instructions configured for;

prompting said at least one user to select said at least one potential site as a user preference; and

storing said user preference in a preference table.

17. The computer-usable medium of claim 15, wherein said dynamic content detection component comprises header based detection, content comparison, non-essential change detection and user selectable content section in order to detect said content updates.

18. The computer-usable medium of claim 15, wherein said plurality of attributes comprises day-of-week, time-of-day, number of visits and a previous website associated with said website.

19. The computer-usable medium of claim 15, wherein said website selection control comprises a standard web browser program with a browser plug-in.

20. The computer-usable medium of claim 15, wherein:

said website selection control comprises a plurality of graphically displayed buttons, such that each graphically displayed button among said plurality of graphically displayed buttons corresponds to a different list of web sites based on said at least one user activity; and

said storage engine comprises a learning component in order to rank said at least one potential website based on said at least one user activity.