System and method for scheduling harvesting of personal information

• US 7,765,279 B1
• Filed: 10/27/1999
• Issued: 07/27/2010
• Est. Priority Date: 10/28/1998
• Status: Expired due to Fees

• Current Assignee: VerticalOne Corp. (Envestnet Incorporated)
• Original Assignee: VerticalOne Corp. (Envestnet Incorporated)
• Inventors: Freishtat, Gregg, Kaib, Paul
• Primary Examiner(s): Winder; Patrice
• Assistant Examiner(s): Mirza; Adnan M
• Application Number:
  US09/427,811
• Time in Patent Office: 3,926 Days
• Field of Search: 707/10, 707/505, 709/203, 709/219, 709/229, 709/226, 709/218, 709/217, 709/224, 705/35, 705/39, 4 4/4
• US Class Current: 709/218
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: G06F 16/954 Navigation, e.g. using categorised browsing
• CPC Class Codes: G06Q 30/00 Commerce
• CPC Class Codes: G06Q 30/04 Billing or invoicing
• CPC Class Codes: G06Q 40/00 Finance; Insurance; Tax strategies; Processing of corporate or income taxes
• CPC Class Codes: H04L 2463/102 applying security measure for e-commerce data processing systems or methods, specially adapted for e-commerce G06Q30/00
• CPC Class Codes: H04L 63/102 Entity profiles
• CPC Class Codes: H04L 67/01 Protocols
• CPC Class Codes: H04L 67/02 based on web technology, e.g. hypertext transfer protocol [HTTP]
• CPC Class Codes: H04L 67/10 in which an application is distributed across nodes in the network software deployment G06F8/60; multiprogramming arrangements G06F9/46
• CPC Class Codes: H04L 67/306 User profiles
• CPC Class Codes: H04L 67/34 involving the movement of software or configuration parameters network booting or remote initial program loading [RIPL] G06F9/4416
• CPC Class Codes: H04L 67/53 using third party service providers
• CPC Class Codes: H04L 67/54 Presence management, e.g. monitoring or registration for receipt of user log-on information, or the connection status of the users
• CPC Class Codes: H04L 67/55 Push-based network services
• CPC Class Codes: H04L 67/56 Provisioning of proxy services store-and-forward switching systems in data switching networks H04L12/54
• CPC Class Codes: H04L 67/563 Data redirection of data network streams
• CPC Class Codes: H04L 67/564 Enhancement of application control based on intercepted application data
• CPC Class Codes: H04L 67/565 Conversion or adaptation of application format or content adding application control or application functional data H04L67/561
• CPC Class Codes: H04L 67/567 Integrating service provisioning from a plurality of service providers
• CPC Class Codes: H04L 69/329 : in the application layer [OSI layer 7]
• CPC Class Codes: H04L 9/40 : Network security protocols

Abstract

This invention is a system and method for a system and method for scheduling the harvesting of information associated with one or more end users from one or more information providers. A host computer, including a processor, is in communication with a user data store for storing data associated with users and an information provider store for storing data associated with information providers. For each end user, a profile of past access times, login times, is maintained in the user data store. For each information provider, a profile of update times and criteria are maintained in the information provider store. For a selected information provider, the host computer processor determines an update time for information stored by the selected information provider and a set of end users whose information could be modified by an update at that update time. The host computer processor generates a predicted login time for each end user in the determined set of end users and each generated login time back a predetermined time interval. The host computer processor sorts the determined set of end users according to the predicted login time or shifted login time and assigns a harvesting time for each end user based on each end user'"'"'s shifted or predicted login time.

Claims

1. A method for scheduling harvesting of information by a host computer from one or more information providers for one or more users, comprising the steps of:

(a) determining an update time for information stored by a selected information provider;

(b) determining a set of end users whose information satisfies a condition for information update at the determined update time;

(c) generating a predicted login time for each end user in the determined set of end users;

(d) sorting the determined set of end users according to the predicted login time generated for each end user in the determined set; and

(e) assigning a harvesting time for each end user based on each end user'"'"'s predicted login time.

2. The method of claim 1, wherein the step of determining a set of end users comprises:

(i) selecting end users configured to receive information from the selected information provider; and

(ii) eliminating end users not configured to receive information subject to update at the determined update time.

3. The method of claim 1, wherein the step of sorting the determined set of end users comprises sorting the determined set in ascending order of predicted login time.

4. The method of claim 1, wherein the step of generating a predicted login time for each end user in the determined set of end users comprises:

(i) for each end user, determining whether a login time profile associated with the end user meets a predetermined confidence threshold;

(ii) for each end user whose login time profile does not meet the predetermined confidence threshold, assigning a predicted login time corresponding to the present day and time; and

(iii) for each end user whose login time profile does meet the predetermined confidence threshold, assigning a predicted login time based on the end user'"'"'s login time profile.

5. The method of claim 1, and further comprising the step of shifting each end user'"'"'s predicted login time back a predetermined time interval.

6. The method of claim 5, wherein the step of assigning a harvest time comprises assigning a harvest time for each end user corresponding to his shifted login time.

7. The method of claim 1, wherein the step of assigning a harvest time comprises:

(i) performing a distribution fit across time to generate a polynomial function that allows determination of the number of end users subject to harvesting over a specified time period;

(ii) determining a network activity curve of network activity associated with the host computer and the selected information provider;

(iii) generating an inverse of the determined network activity curve;

(iv) performing an integral matching algorithm utilizing the generated polynomial function and the generated inverse of the network activity curve; and

(v) assigning harvesting times for each end user to redistribute peak harvesting time towards time zero to flatten the distribution fit across time.

8. The method of claim 1, and further comprising the step of harvesting the information for each end user in the determined set of end user from the selected information provider at the harvesting time assigned to each end user.

9. The method of claim 1, wherein information is personal information.

10. The method of claim 9, wherein personal information is personal financial information or personal communication information.

11. The method of claim 10, wherein personal financial information is information from at least one of billing information, financial account information, investment information, 401(k) information, benefits information, credit information, or mortgage information.

12. The method of claim 10, wherein personal communication information is information from at least one of an email message, voice message, or fax message.

13. A method for scheduling harvesting of personal information by a host computer from one or more information providers for one or more users, comprising the steps of:

(a) determining an update time for personal information stored by a selected information provider;

(b) determining a set of end users whose personal information satisfies a condition for information update at the determined update time;

(c) generating a predicted login time for each user as a function of the end user'"'"'s login time profile and a predetermined confidence threshold;

(d) sorting the determined set of end users according to the predicted login time generated for each end user in the determined set; and

(e) assigning a harvesting time for each end user based on each end user'"'"'s predicted login time.

14. The method of claim 13, wherein personal information is personal financial information or personal communication information.

15. The method of claim 14, wherein personal financial information is information from at least one of billing information, financial account information, investment information, 401(k) information, benefits information, credit information, or mortgage information.

16. The method of claim 14, wherein personal communication information is information from at least one of an email message, voice message, or fax message.

17. The method of claim 13, wherein the step of generating a predicted login time comprises the steps of:

i) for each end user, determining whether a login time profile associated with the end user meets a predetermined confidence threshold;

ii) for each end user whose login time profile does not meet the predetermined confidence threshold, generating a predicted login time from within a predetermined range of the present day and time; and

iii) for each end user whose login time profile does meet the predetermined confidence threshold, generating a predicted login time based on the end user'"'"'s login time profile.

18. The method of claim 13, wherein the step of determining a set of end users comprises:

i) selecting end users configured to receive personal information from the selected information provider; and

ii) eliminating end users not configured to receive personal information subject to update at the determined update time.

19. The method of claim 13, wherein the step of sorting the determined set of end users comprises sorting the determined set in ascending order of predicted login time.

20. The method of claim 13, further comprising the step of harvesting the personal information for each end user in the determined set of end user from the selected information provider at the harvesting time assigned to each end user.

21. The method of claim 13, wherein the step of assigning a harvest time comprises:

i) determining the number of end users subject to harvesting over a specified time period;

ii) determining a network activity curve of network activity associated with the host computer and the selected information provider;

iii) performing a matching algorithm utilizing the determined number of end users and the network activity curve; and

iv) assigning harvesting times for each end user to redistribute peak harvesting times in order to minimize network utilization.

22. A method for scheduling harvesting of personal information by a host computer from one or more information providers for one or more users, comprising the steps of:

(a) determining an update time for personal information stored by a selected information provider;

(b) determining a set of end users whose personal information satisfies a condition for information update at the determined update time;

(c) generating a predicted login time for each end user in the determined set of end users;

(d) sorting the determined set of end users according to the predicted login time generated for each end user in the determined set; and

(e) assigning a harvesting time for each end user based on each end user'"'"'s predicted login time, by performing the steps of;

i) determining the number of end users subject to harvesting over a specified time period;

ii) determining a network activity curve of network activity associated with the host computer and the selected information provider; and

iii) assigning harvesting times for each end user using the determined number of users and the network activity curve in order to optimize the network bandwidth used for harvesting.

23. The method of claim 22, wherein the step of determining a set of end users comprises:

i) selecting end users configured to receive personal information from the selected information provider; and

ii) eliminating end users not configured to receive personal information subject to update at the determined update time.

24. The method of claim 22, wherein the step of sorting the determined set of end users comprises sorting the determined set in ascending order of predicted login time.

25. The method of claim 22, further comprising the step of harvesting the personal information for each end user in the determined set of end user from the selected information provider at the harvesting time assigned to each end user.

26. The method of claim 22, wherein the step of assigning a harvesting time comprises the steps of

i) performing a distribution fit across time to generate a polynomial function that allows determination of the number of end users subject to harvesting over a specified time period;

ii) determining a network activity curve of network activity associated with the host computer and the selected information provider;

iii) generating an inverse of the determined network activity curve;

iv) performing an integral matching algorithm utilizing the generated polynomial function and the generated inverse of the network activity curve; and

v) assigning harvesting times for each end user to redistribute peak harvesting time towards time zero to flatten the distribution fit across time.

27. The method of claim 22, wherein the step of generating a predicted login time comprises the steps of:

i) for each end user, determining whether a login time profile associated with the end user meets a predetermined confidence threshold; and

ii) for each end user, generating a predicted login time as a function of the end user'"'"'s login time profile and confidence threshold.

28. The method of claim 22, wherein personal information is personal financial information or personal communication information.

29. The method of claim 28, wherein personal financial information is information from at least one of billing information, financial account information, investment information, 401(k) information, benefits information, credit information, or mortgage information.

30. The method of claim 28, wherein personal communication information is information from at least one of an email message, voice message, or fax message.