Method and apparatus for collecting and disseminating information over a computer network

• US 9,047,483 B2
• Filed: 09/20/2013
• Issued: 06/02/2015
• Est. Priority Date: 09/07/2000
• Status: Expired due to Fees

• Current Assignee: mBlast, Inc.
• Original Assignee: mBlast, Inc.
• Inventors: Briere, Daniel D., Pritchard, Paul W.
• Primary Examiner(s): Eskandarnia, Arvin
• Application Number:
  US14/033,099
• Publication Number:
  US 20140019204A1
• Time in Patent Office: 620 Days
• Field of Search: 709/201, 709/202, 709/203, 709/210, 709/219, 707600-603, 705342-344
• US Class Current: 1/1
• CPC Class Codes: G06F 16/2379 Updates performed during online database operations; commit processing
• CPC Class Codes: G06F 16/24578 using ranking
• CPC Class Codes: G06F 16/248 Presentation of query results
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: G06F 16/9538 Presentation of query results
• CPC Class Codes: G06F 16/955 using information identifiers, e.g. uniform resource locators [URL]
• CPC Class Codes: G06F 16/958 Organisation or management of web site content, e.g. publishing, maintaining pages or automatic linking
• CPC Class Codes: G06F 16/972 Access to data in other repository systems, e.g. legacy data or dynamic Web page generation
• CPC Class Codes: G06F 16/986 Document structures and storage, e.g. HTML extensions
• CPC Class Codes: G06F 21/6236 between heterogeneous systems
• CPC Class Codes: G06F 2221/2129 Authenticate client device independently of the user
• CPC Class Codes: G06F 40/174 Form filling; Merging
• CPC Class Codes: G06Q 10/0631 Resource planning, allocation, distributing or scheduling for enterprises or organisations
• CPC Class Codes: G06Q 10/10 Office automation; Time management
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0201 Market modelling; Market analysis; Collecting market data
• CPC Class Codes: G06Q 30/0204 Market segmentation
• CPC Class Codes: H04L 63/102 Entity profiles
• CPC Class Codes: H04L 65/1059 End-user terminal functionalities specially adapted for real-time communication
• 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 67/1097 : for distributed storage of data in networks, e.g. transport arrangements for network file system [NFS], storage area networks [SAN] or network attached storage [NAS]
• CPC Class Codes: H04L 67/30 : Profiles
• CPC Class Codes: H04L 67/306 : User profiles
• CPC Class Codes: H04L 67/51 : Discovery or management thereof, e.g. service location protocol [SLP] or web services
• CPC Class Codes: H04L 67/52 : specially adapted for the location of the user terminal
• CPC Class Codes: H04L 67/55 : Push-based network services
• CPC Class Codes: H04L 67/63 : Routing a service request depending on the request content or context

Abstract

The apparatus comprises at least one database for storing digital information associated with at least a first user and a second user, at least one links module for the first user and for the second user, at least one manipulations module and at least one display device for respectively displaying at least said linked digital information wherein said linked digital information associated with said first user is automatically updated on at least said display device of said second user when that information is manipulated, and wherein said linked digital information associated with said second user is automatically updated on at least said display device of said first user when that information is manipulated.

Claims

1. An apparatus, comprising:

a retrievers module implemented in at least one of a memory or a processing device, the retrievers module configured to access a computer network, the retrievers module configured to identify content published by a second party within the computer network and associated with content published by a first party within the computer network;

a market presence module operably coupled to the retrievers module, the market presence module configured to select a portion of content from the content published by the second party based at least in part on a keyword associated with at least one of the first party or the second party, the market presence module configured to quantify a degree of presence within the computer network and associated with the portion of content based at least in part on the content published by the first party, the market presence module configured to quantify an influence value associated with at least one of the first party or the second party based at least in part on the degree of presence.

2. The apparatus of claim 1, wherein the degree of presence is based at least in part on a comparison of the content published by the first party and the content published by the second party.

3. The apparatus of claim 1, wherein the degree of presence is based at least in part on a set of metadata associated with the first party and a set of metadata associated with the second party.

4. The apparatus of claim 1, wherein the influence value is based at least in part on a comparison of the content published by the first party and the content published by the second party.

5. The apparatus of claim 1, further comprising:

a presentation module operably coupled to the retrievers module and the market presence module, the presentation module configured to receive the keyword from a user.

6. The apparatus of claim 1, wherein the market presence module is configured to send a signal representing at least one of the degree of presence or the influence value.

7. The apparatus of claim 1, wherein the market presence module is configured to send a signal representing at least one of the degree of presence or the influence value to a display module such that the at least one of the degree of presence or the influence value is displayed in the display module.

8. The apparatus of claim 1, wherein the market presence module is configured to send a signal representing the influence value associated with the second party and a signal representing identification of the second party.

9. The apparatus of claim 1, wherein the market presence module is configured to send, to a third party, a signal representing the influence value associated with the second party and representing identification of the second party, such that the third party contacts the second party.

10. The apparatus of claim 1, wherein the market presence module is configured to detect a topic from a plurality of predefined topics based at least in part on at least one of the content published by the first party or the content published by the second party, the market presence module configured to quantify a relevance value based at least in part on the topic and at least in part on the content published by the second party, the relevance value being associated with the second party.

11. The apparatus of claim 1, wherein the market presence module is configured to detect an attitude from a plurality of predefined attitudes based at least in part on at least one of the content published by the first party or the content published by the second party, the attitude being associated with the second party.

12. The apparatus of claim 1, wherein the market presence module is configured to detect an attitude from a plurality of predefined attitudes based at least in part on at least one of the content published by the first party or the content published by the second party, the attitude being associated with the second party and the keyword.

13. The apparatus of claim 1, wherein the market presence module is configured to detect an attitude from a plurality of predefined attitudes associated with a topic, the topic being associated with at least one of the content published by the first party or the content published by the second party.

14. The apparatus of claim 1, wherein the market presence module is configured to quantify a relevance value based at least in part on the keyword and at least in part on the content published by the second party, the relevance value being associated with the second party.

15. A non-transitory processor-readable medium storing code representing instructions to be executed by a processor, the code comprising code to cause the processor to:

identify content published by a second party within a computer network and associated with content published by a first party within the computer network;

select a portion of the content published by the second party based at least in part on a keyword associated with the content published by the first party;

quantify a degree of presence within the computer network and associated with the portion of content based at least in part on the content published by the first party; and

quantify an influence value associated with at least one of the first party or the second party based at least in part on the degree of presence.

16. The non-transitory processor-readable medium of claim 15, further comprising code to cause the processor to send a signal representing at least one of the degree of presence or the influence value to a display module such that at least one of the degree of presence or the influence value is displayed on the display module.

17. The non-transitory processor-readable medium of claim 15, further comprising code to cause the processor to send, to the first party, a signal representing the influence value associated with the second party and a signal representing identification of the second party such that the first party contacts the second party.

18. The non-transitory processor-readable medium of claim 15, wherein the degree of presence is based at least in part on a set of metadata associated with the first party and a set of metadata associated with the second party.

19. The non-transitory processor-readable medium of claim 15, wherein the selection of a portion of the content published by the second party is based at least in part on a set of metadata associated with the second party.

20. The non-transitory processor-readable medium of claim 15, further comprising code to cause the processor to:

detect a topic from a plurality of predefined topics based at least in part on at least one of the content published by the first party or the content published by the second party; and

quantify a relevance value based at least in part on the topic and at least in part on the content published by the second party, the relevance value being associated with the second party.

21. The non-transitory processor-readable medium of claim 15, further comprising code to cause the processor to detect an attitude from a plurality of predefined attitudes based at least in part on at least one of the content published by the first party or the content published by the second party, the attitude being associated with the second party and the keyword.

22. The non-transitory processor-readable medium of claim 15, further comprising code to cause the processor to detect an attitude from a plurality of predefined attitudes associated with a topic, the topic being associated with at least one of the content published by the first party or the content published by the second party.

23. The non-transitory processor-readable medium of claim 15, wherein the selection of a portion of content published by the second party is based on a set of metadata from a first source associated with the second party and a set of metadata from a second source associated with the second party, the first source being different than the second source.

24. A non-transitory processor-readable medium storing code representing instructions to be executed by a processor, the code comprising code to cause the processor to:

identify content published by a second party within a computer network and associated with content published by a first party within the computer network;

select a portion of the content published by the second party based at least in part on a keyword associated with the content published by the first party; and

quantify an influence value associated with at least one of the first party or the second party based at least in part on a set of metadata associated with the first party and a set of metadata associated with the second party.

25. The non-transitory processor-readable medium of claim 24, wherein the set of metadata associated with the first party is associated with a first source, the set of metadata associated with the second party is associated with a second source different than the first source.

26. The non-transitory processor-readable medium of claim 24, further comprising code to cause the processor to catalogue at least one of the content published by the first party or the content published by the second party, based at least in part on at least one of (1) metadata associated with the content published by the first party and from the set of metadata associated with the first party, or (2) metadata associated with the content published by the second party and from the set of metadata associated with the second party.

27. The non-transitory processor-readable medium of claim 24, further comprising code to cause the processor to send a signal representing at least one of the set of metadata associated with the first party or the set of metadata associated with the second party.

28. The non-transitory processor-readable medium of claim 24, further comprising code to cause the processor to:

detect a topic from a plurality of predefined topics based at least in part on the set of metadata associated with the first party and the set of metadata associated with the second party; and

quantify a relevance value based at least in part on the topic and at least in part on the set of metadata associated with the second party, the relevance value associated with the second party.