COLLECTIONS OF LINKED DATABASES

• US 20080228947A1
• Filed: 03/15/2007
• Published: 09/18/2008
• Est. Priority Date: 09/15/2004
• Status: Active Grant

• Current Assignee: 3degrees LLC
• Original Assignee: 3degrees LLC
• Inventors: Smith, Brian N., Markus, Michael J., McGuire, Heather A., Kionga-Kamau, Peter M.
• Granted Patent: US 8,635,217 B2
• Time in Patent Office: Days
• US Class Current: 709/217
• CPC Class Codes: G06F 16/906 Clustering; Classification
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques
• CPC Class Codes: G06F 16/9536 Search customisation based on social or collaborative filtering

Abstract

This invention is generally directed to one or more methods or systems relating to inferential networks. This invention is further directed to methods and systems for making and using inferential networks. Still further, this invention is generally directed to making one or more inferential networks by using data generated from directed searches of collections of linked databases.

Claims

1. A method for making an inferential network of electronic databases, the method comprising the steps of:

storing electronic search data comprising a record of search terms used in searches of collections of linked databases and electronic databases returned from the searches;

creating an inferential link between a first inferential-network node and a second inferential-network node, wherein the inferential link is created as a function of the electronic search data;

wherein the inferential network is created by storing one or more inferential links between inferential-network nodes.

2. The method of claim 1, wherein the search data is selected from the group consisting of search data from searches conducted using an anchor database, broadcast-search data, and a combination of broadcast-search search data and search data from searches conducted using an anchor database.

3. The method of claim 1, wherein the inferential network nodes are members of a social network.

4. The method of claim 1, wherein the inferential network nodes are internet or intranet websites.

5. The method of claim 4, wherein the first inferential-network node represents a search initiator that has initiated a search of a collection of linked databases with a designated anchor database, and the second inferential-network node represents an anchor database.

6. The method of claim 1, wherein the first inferential-network node represents a search initiator that has selected a database from among search results;

and the second inferential-network node represents either a database selected by the search initiator from the search results or an anchor database that was designated as part of the search.

7. The method of claim 6, wherein the collection of linked databases is selected from the group consisting of a collection of linked websites on the internet, a collection of linked websites on an intranet system, a collection of linked nodes in a social-network map, and a combination thereof.

8. The method of claim 1, wherein the inferential link is a subject-matter based qualification derived from a search term used in a search that included a designated anchor database.

9. The method of claim 5, wherein the anchor database is a node in an inferential network.

10. The method of claim 1, further comprising the step of assigning a strength variable to the inferential link.

11. The method of claim 10, wherein the step of assigning a strength variable comprises a step selected from the group consisting of:

decreasing the strength of the variable as a function of time;

increasing the strength of the variable as a function of a number of times that a node associated with the link is designated as an anchor database; and

increasing the strength of the variable as a function of a number of times that a node associated with the inferential link is designated as an anchor database in a search for an identical or related search term.

12. The method of claim 9, further comprising the step of qualifying a node in the inferential network as a function of the strength variable of an inferential link associated with the node.

13. The method of claim 12, further comprising the step of qualifying the node as a node representing a database that is most likely to have information on a search topic relative to other databases represented by nodes in the inferential network.

14. The method of claim 12, further comprising the step of qualifying the node as a node representing a database that is more likely than not to have information on a search topic relative to other databases represented by nodes in an inferential network.

15. The method of claim 1, further comprising the steps of assigning a strength variable to the node, and varying the strength variable by one of the following steps:

varying the strength variable as a function of a number of times that the node is designated as an anchor database in a search for an identical or related search term;

varying the strength variable as a function of a number of unique search initiators that have designated the node as an anchor database.

16. A method for establishing an inferential-network path, the method comprising the steps of:

parsing an inferential network to determine a link or links connecting a first inferential-network node to a second inferential-network node;

establishing an inferential-network path from the first inferential-network node to the second inferential-network node, wherein the path is selected from one or more paths in an inferential network.

17. The method of claim 16, wherein the first inferential-network node represents an inferential-network search initiator and the second inferential-network node represents a database that is most likely to have information on a search topic relative to other databases represented by nodes in the inferential network.

18. The method of claim 16, wherein the path has the least number of intervening nodes between the first inferential-network node and the second inferential-network node relative to other inferential-network paths from the first inferential-network node to the second inferential-network node.

19. The method of claim 16, wherein the path is determined as a function of a strength variable assigned to the links between the first and second nodes.

20. The method of claim 16, wherein the sum of the strengths of the inferential links in the path is the greatest relative to other inferential-network paths having the least number of intervening nodes between the first inferential-network node and the second inferential-network node.

21. The method of claim 16, wherein the path is determined by substituting a first portion of an inferential network into a second portion of the inferential network, wherein the first and second portions have inferential links qualified with different subject matter topics.

22. A method for displaying a portion of an inferential network, the method comprising the steps of:

accessing an inferential network wherein links are established between two or more nodes according to one or more qualifications;

displaying at least a portion of the inferential network, wherein the portion of the inferential network is made up at least in part by a section having the form;

wherein “

D₁”

is a first inferential-network node,

wherein “

D₂”

is a second inferential-network node,

wherein “

-”

represents an inferential link between D₁ and D₂,

wherein “

c”

represents a visual designation of the “

-”

link between the first inferential-network node and the second inferential-network node, and

wherein the visual designation of the “

-”

link qualifies the link as any of two or more link qualifications.

23. The method of claim 22, wherein “

c”

is based at least in part upon a strength variable assigned to the inferential link between D₁ and D₂.

24. The method of claim 23, further comprising the step of:

displaying the portion of the inferential network as at least a part of the results of searching an inferential network for a search term, wherein the first inferential-network node is a node representing a search initiator and a second inferential-network node is a node containing the search term.

25. The method of claim 24, wherein the search includes a multi-term search of the network using one search term or phrase, wherein the one search term or phrase initiates the use of one or more second search terms or search phrases in the search.

26. The method of claim 24, wherein the results are ordered as a function of the qualifications or strength of one or more inferential links between the first node and the second node.

27. The method of claim 24, further comprising the steps of:

using a first portion of a visual display screen to display the results of the inferential-network search; and

using a second portion of the visual display screen to display the portion of the inferential network;

wherein the portion of the inferential network includes the first node and the second node and any intervening nodes.

28. A method for ordering search results using inferential network data comprising:

searching an electronic database for a search term;

retrieving stored inferential network data;

weighting the results of the search as a function of the inferential network data; and

displaying the results of the search ordered according to the weighting.