System and method for a search engine content filter

• US 10,324,598 B2
• Filed: 08/21/2015
• Issued: 06/18/2019
• Est. Priority Date: 12/18/2009
• Status: Active Grant

• Current Assignee: Graphika Technologies Incorporated
• Original Assignee: Graphika, Inc.
• Inventors: Kelly, John W., Barash, Vladimir D., Fields, Adam
• Primary Examiner(s): Hoang, Son T
• Application Number:
  US14/832,106
• Publication Number:
  US 20160048556A1
• Time in Patent Office: 1,397 Days
• Field of Search: None
• CPC Class Codes: G06F 16/212 with details for data modelling support
• CPC Class Codes: G06F 16/278 Data partitioning, e.g. horizontal or vertical partitioning
• CPC Class Codes: G06F 16/285 Clustering or classification
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: G06F 3/04842 Selection of displayed objects or displayed text elements G06F3/0482 takes precedence
• CPC Class Codes: G06Q 10/10 Office automation; Time management
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising

Abstract

Computerized search methods and systems generally include presenting, to a user, a computer interface for specifying one or more search terms for a search query and presenting at least one selectable item corresponding to at least one of art M score and a cluster focus index (CFI) score filter for the search query. The methods and systems include generating an amended search query based on a selected item; and performing a search using the amended search query. The M score is calculated using the formula M score=count (alpha)+CFI (1-alpha), where the count is the overall number of members on a cluster focus map that has engaged with a target.

Claims

1. A computerized search method, the method comprising:

presenting, to a user, a computer interface for specifying one or more search terms for a search query;

presenting at least one selectable item through the computer interface corresponding to at least one of an M score and a cluster focus index score (CFI) for the search query, wherein the CFI represents a degree to which a particular target is disproportionately cited in a particular cluster;

generating an amended search query based on a selected item; and

performing a search through the computer interface using the amended search query, wherein the M score is calculated using a formula of M score=count(alpha)+CFI(1-alpha), where the count is an overall number of members of the particular cluster that has engaged with the particular target, and values of alpha being between 0 and 1.

2. The method of claim 1, wherein the search is of the Internet.

3. The method of claim 1, wherein the search is of a CFI-filtered set of clusters within an online network.

4. The method of claim 1, wherein the search is of a set of nodes having the M score greater than a threshold.

5. The method of claim 1, wherein the search is of a document-corpus.

6. The method of claim 1, wherein the CFI further represents a degree to which an event, characteristic or behavior disproportionately occurs in the particular cluster, or a degree to which the particular cluster, relative to a network, preferentially manifests the event, characteristic or behavior.

7. The method of claim 1, wherein the computer interface is configured for the user to select content to search with the one or more search terms.

8. The method of claim 7, wherein the content is taken from an online creator network partitioned into at least one set of source nodes.

9. The method of claim 8, wherein the at least one set of source nodes is configured with a similar linking history to form an attentive cluster and at least one set of outlink targets with a similar citation profile to form an outlink bundle.

10. The method of claim 8, further comprising performing a search of the selected content using the search query.

11. The method of claim 1, further comprising:

generating a list of targets in a network, cluster, or segment; and

filtering the list by criteria to limit whom to a message in the network, cluster, or segment in order to maximize the impact of the message on the cluster or segment.

12. The method of claim 11, wherein the filtering the list by the criteria includes filtering by at least one of the CFI score, the M score, a number of followers, a following status, a follower status, a number of mentions or re-tweets, a number of distinct mentions, a status of exposure to content, and a frequency of tweets or publication.

13. The method of claim 12, wherein the generating of the list of targets in the network, cluster, or segment includes using at least one of the CFI score, the M score, the number of followers, the number of mentions or re-tweets, a number of distinct mentions, and a number of tweets.

14. The method of claim 13, wherein the M score is based on the CFI that further details a degree to which the particular target disproportionately occurs in the particular cluster, or a degree to which the particular cluster, relative to a network, preferentially engages with the particular target, wherein an overall number of members of the cluster or network that have engaged with the particular target is determined.

15. A method for automatically analyzing and determining whether an overall number of members have engaged with a target, the method comprising:

presenting, to a user, a computer interface hosted by a computing device, wherein the computer interface is configured to specify one or more search terms for a search query;

presenting on the computer interface at least one selectable item corresponding to at least one of an M score and a cluster focus index score (CFI) for the search query, wherein the CFI represents a degree to which a particular target is disproportionately cited in a particular cluster;

generating an amended search query with the computing device based the at least one selectable item; and

performing a search on the computer interface with the computing device using the amended search query, wherein the M score is calculated using a formula of M score=count(alpha)+CFI(1-alpha), where the count is an overall number of members of the particular cluster that has engaged with the particular target, and values of alpha being between 0 and 1.

16. The method of claim 15, wherein the search is of the Internet.

17. The method of claim 15, wherein the search is of a CFI-filtered set of clusters within an online network.

18. The method of claim 15, wherein the search is of a set of nodes having the M score greater than a threshold.

19. The method of claim 15, wherein the search is of a document-corpus.

20. The method of claim 15, wherein the CFI further represents a degree to which an event, characteristic or behavior disproportionately occurs in the particular cluster, or a degree to which the particular cluster, relative to a network, preferentially manifests the event, characteristic or behavior.

21. The method of claim 15, wherein the computer interface is configured for the user to select content to search with the one or more search terms, and wherein the content is taken from an online creator network partitioned into at least one set of source nodes.

22. The method of claim 21, wherein the at least one set of source nodes is configured with a similar linking history to form an attentive cluster and at least one set of outlink targets with a similar citation profile to form an outlink bundle.