METHOD AND SYSTEM FOR RELATIONSHIP MANAGEMENT AND INTELLIGENT AGENT

• US 20120150888A1
• Filed: 06/11/2011
• Published: 06/14/2012
• Est. Priority Date: 09/10/2003
• Status: Abandoned Application

• Current Assignee: Thomson Reuters Global Resources
• Original Assignee: Thomson Reuters Global Resources
• Inventors: Hyatt, Geoffrey, Swan, Wilbur, Samuel, Shawn
• Application Number:
  US13/158,408
• Publication Number:
  US 20120150888A1
• Time in Patent Office: Days
• US Class Current: 707/758
• CPC Class Codes: G06F 16/242 Query formulation
• CPC Class Codes: G06F 16/24575 using context
• CPC Class Codes: G06F 16/288 Entity relationship models
• CPC Class Codes: G06F 16/335 Filtering based on additional data, e.g. user or group profiles filtering in web context G06F16/9535, G06F16/9536
• CPC Class Codes: G06F 16/337 Profile generation, learning or modification
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: G06F 16/9536 Search customisation based on social or collaborative filtering
• CPC Class Codes: G06F 21/6227 where protection concerns the structure of data, e.g. records, types, queries
• CPC Class Codes: G06F 21/6254 by anonymising data, e.g. decorrelating personal data from the owner's identification
• CPC Class Codes: G06Q 10/107 Computer-aided management of electronic mailing [e-mailing]
• CPC Class Codes: G06Q 30/0269 based on user profile or attribute

Abstract

The present invention provides computer-based systems and methods directed to maintaining a database of user profiles based, respectively, on user interaction with third-party systems. The invention includes the processes of: accessing a unique user profile associated with a unique user; automatically collecting, by an agent module executing on a processor associated with a first system, data associated with the unique user based at least in part on the unique user'"'"'s interaction with a system unassociated with the first system; evaluating by the processor the collected data and searching available databases to identify potential items of interest to the unique user based at least in part on the unique user profile and the collected data; determining a set of predicted items of interest to the unique user from the identified potential items of interest; and presenting at a display associated with the unique user data representing the set of predicted items of interest. In one implementation, the invention provides an intelligent agent possessing a level of “awareness” concerning individual users associated with user profiles or accounts and is adapted to access private and public databases, websites, resources, and other systems to efficiently collect, filter and deliver/present content and resources of interest to the individual user in a predictive fashion.

Claims

1. A computer-implemented method of maintaining a database of user profiles based, respectively, on user interaction with third-party systems, the method comprising:

accessing a unique user profile associated with a unique user;

automatically collecting, by an agent module executing on a processor associated with a first system, data associated with the unique user based at least in part on the unique user'"'"'s interaction with a system unassociated with the first system;

evaluating by the processor the collected data and searching available databases to identify potential items of interest to the unique user based at least in part on the unique user profile and the collected data;

determining a set of predicted items of interest to the unique user from the identified potential items of interest; and

presenting at a display associated with the unique user data representing the set of predicted items of interest.

2. The method of claim 1, wherein automatically collecting by an agent module data associated with the unique user includes accessing and searching user account data associated with the unique user.

3. The method of claim 2, wherein the user account data includes one or more of email, calendar, contacts, and phone record accounts.

4. The method of claim 3, wherein the user account data includes one or more of:

an entry in a calendar program indicating a scheduled meeting with a first entity;

a contact record representing the first entity;

an email including an email address associated with the first entity;

and an email containing a name or other identifier associated with the first entity;

a billing system entry containing client, billing, time or related data;

a customer relationship management (CRM) system entry containing contact, company, activity or related data;

a phone call record;

a travel system entry containing travel plans, reservations and related data;

click stream data; and

application usage data.

5. The method of claim 3, wherein the set of predicted items of interest to the unique user includes content concerning a first entity, the content being one or more of biography, article, caselaw, website, regulatory filing, financial reporting, transcripts, interviews, competitive intelligence, trading data, related analytics, third-party reports, and related internal data, such as CRM activities, experience data and related proposals.

6. The method of claim 1, wherein the collecting by an agent module data associated with the unique user includes accessing and searching data maintained within an organization.

7. The method of claim 1, wherein the evaluating collected data and searching available databases includes accessing databases outside of an organization associated with the unique user.

8. The method of claim 1, wherein the evaluating collected data and searching available databases includes accessing one or more of:

publicly available content database;

subscriber-based content database;

fee-based content database;

professional service provider content database;

government maintained database; and

regulatory database.

9. The method of claim 8, wherein evaluating collected data and searching available databases includes using secure sign-in data associated with the unique user to automatically access a database via a secure sign-in procedure.

10. The method of claim 9, wherein the secure sign-in data includes user login identifier and password data associated with the unique user.

11. The method of claim 8, wherein evaluating collected data and searching available databases includes using user profiles associated with one or more of professional networking sites (e.g., LinkedIn) and social networking sites (e.g., Facebook, MySpace) to collect professional and/or personal data associated with the user or an entity linked to the user.

12. The method of claim 11 further comprising accessing one or more user profiles associated with one or more of professional and social networking sites to collect professional and/or personal data associated with the user associated with the one or more user profiles.

13. The method of claim 1 further comprising:

determining based at least in part on the collected data a first entity, the set of predicted items of interest being related to the first entity.

14. The method of claim 13, wherein determining based at least in part on the collected data a first entity includes evaluating the strength of relationship between the first entity and the unique user.

15. The method of claim 13, wherein the collected data includes contact information associated with the first entity, unique user information and one or more values related to strength of relationship between the first entity and the unique user.

16. The method of claim 13, wherein determining based at least in part on the collected data a first entity includes comparing the first entity with an authority database to validate the identity of the first entity.

17. The method of claim 13, wherein determining based at least in part on the collected data a first entity includes comparing the first entity with one or more databases to determine a confidence level used to associate the first entity with a known entity.

18. The method of claim 13, wherein determining based at least in part on the collected data a first entity further comprises performing a disambiguation process on the first entity to validate the identity of the first entity.

19. The method of claim 13, wherein determining based at least in part on the collected data a first entity further comprises performing a data cleansing to eliminate false positive identification of entities.

20. The method of claim 1, wherein determining a set of predicted items of interest to the unique user from the identified potential items of interest includes performing one or more of Bayesian, idf, and TF-idf, processes on the identified potential items of interest.

21. The method of claim 1, wherein determining a set of predicted items of interest to the unique user from the identified potential items of interest includes performing, in a network-wide context, analysis of entities extracted from the item.

22. The method of claim 1, wherein presenting the unique user with data representing the set of predicted items of interest includes presenting links to one or more of document, webpage, contact data, profile data, email data, calendar data, and database.

23. The method of claim 1, wherein presenting the unique user with data representing the set of predicted items of interest includes automatically generating and transmitting an email to an email account associated with the unique user.

24. The method of claim 1, wherein presenting the unique user with data representing the set of predicted items of interest includes automatically incorporating into a calendar event associated with the unique user a set of one or more links to one or more of the predicted items of interest.

25. The method of claim 1, wherein presenting the unique user with data representing the set of predicted items of interest includes automatically generating and presenting via a user dashboard associated with the unique user links to one or more of the predicted items of interest.

26. The method of claim 1 further comprising presenting the unique user with a user interface adapted to enable the unique user to dynamically select and/or deselect certain ones of the predicted items of interest.

27. The method of claim 1 further comprising the unique user taking an action related to the predicted items of interest and collecting data associated with the user action and updating the user profile based on the collected data associated with the user action.

28. The method of claim 1, wherein the method is performed in either a periodic or a real-time manner.

29. The method of claim 1 further comprising building a user profile via algorithms to segment and rank the areas of interest to a given user.

30. The method of claim 29 further comprising modifying the user profile based on user'"'"'s reactions to the presented data.

31. The method of claim 29 further comprising identifying similar user profiles as a potential additional source of predicted items of interest, based on users'"'"' reactions to presented data.

32. The method of claim 1 further comprising accessing by a first external provider system a first user profile maintained by the database.

33. The method of claim 1 further comprising receiving data derived from a first external provider system and concerning an entity associated with a first user profile maintained by the database.

34. The method of claim 33 further comprising revising the first user profile based on the data received from the first external provider system.

35. A computer-implemented system for maintaining a database of user profiles based, respectively, on user interaction with third-party systems, the system comprising:

a server comprising a processor and a memory adapted to store executable program instructions and data;

a database comprising a plurality of user profiles, each user profile being unique and being associated with a unique user entity, the server adapted to access the database and to receive inputs;

an agent module comprising a first set of code executable by the processor and adapted to process data associated with the unique user based at least in part on the unique user'"'"'s interaction with an unassociated system;

a second set of executable code adapted to evaluate collected data and search available databases to identify potential items of interest to the unique user based at least in part on the unique user profile and the collected data;

a third set of executable code adapted to determine a set of predicted items of interest to the unique user from the identified potential items of interest; and

a fourth set of executable code adapted to present at a display associated with the unique user data representing the set of predicted items of interest.

36. The system of claim 35 further comprising means for accessing by a first external provider system a first user profile maintained by the database.

37. The system of claim 35 further comprising means for receiving data derived from a first external provider system and concerning an entity associated with a first user profile maintained by the database.

38. The system of claim 35 wherein the system revises the first user profile based on the data received from the first external provider system.

39. A computer-readable medium comprising code adapted to maintain a database of user profiles based, respectively, on user interaction with third-party systems, the code being executable by a server comprising a processor and a memory adapted to store executable program instructions and being in communication with an associated database comprising a plurality of user profiles, each user profile being unique and being associated with a unique user entity, the server adapted to access the database and to receive inputs, the computer-readable medium comprising:

an agent module comprising a first set of code executable by the processor and adapted to process data associated with the unique user based at least in part on the unique user'"'"'s interaction with an unassociated system;

a second set of executable code adapted to evaluate collected data and search available databases to identify potential items of interest to the unique user based at least in part on the unique user profile and the collected data;

a third set of executable code adapted to determine a set of predicted items of interest to the unique user from the identified potential items of interest; and

a fourth set of executable code adapted to present at a display associated with the unique user data representing the set of predicted items of interest.