IP Library Granted Patent US 8,954,458
Granted Patent B2
US 8,954,458 · App. 13/179,940 · Granted Feb 10, 2015

Systems and methods for providing a content item database and identifying content items

View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 8,954,458
App. No.
13/179,940
Granted
Feb 10, 2015
Kind
B2
Abstract

Systems and methods are provided for identifying unsolicited or unwanted electronic communications, such as spam. The disclosed embodiments also encompass systems and methods for selecting content items from a content item database. Consistent with certain embodiments, computer-implemented systems and methods may use a clustering based statistical content matching anti-spam algorithm to identify and filter spam. Such a anti-spam algorithm may be implemented to determine a degree of similarity between an incoming e-mail with a collection of one or more spam e-mails stored in a database. If the degree of similarity exceeds a predetermined threshold, the incoming e-mail may be classified as spam. Further, in accordance with other embodiments, systems and methods may be provided to determine a degree of similarity between a query or search string from a user and content items stored in a database. If the degree of similarity exceeds a predetermined threshold, the content item from the database may be identified as a content item that matches the query or search string provided by the user.

Claims (70)

1. A computer-implemented method of selecting a content item from a content item database, the method comprising:

accessing an incoming query from a memory device;

creating a first set of tokens from the incoming query;

computing a first total as a number of tokens in the first set of tokens;

accessing a second set of tokens corresponding to the content item stored in the content item database;

determining, with at least one processor, a degree of similarity by:

determining a minimum of a first count and a second count, the first count being a count of a unique token in the first set of tokens and the second count being a count of the unique token in the second set of tokens;

computing a randomized easy signature by:

selecting a set of most frequent tokens from the second set of tokens;

computing a second total as a number of tokens in the selected set of most frequent tokens;

randomly selecting a sub-set of tokens from the selected set of most frequent tokens;

determining a number of common tokens based on a minimum of the first count and a third count, the third count being a count of the unique token in the randomly selected sub-set of tokens; and

determining the randomized easy signature as a ratio of the number of common tokens and a sum of the first total and the second total; and

selecting, with the at least one processor, the content item as matching the incoming query if the degree of similarity exceeds a predetermined threshold.

2. The computer-implemented method of claim 1 , wherein the incoming query comprises at least one of a search string and a user query.

3. The computer-implemented method of claim 1 , wherein creating the first set of tokens comprises:

processing the incoming query by changing an upper-case letter into a lower-case letter and removing a space; and

creating the first set of tokens from the processed incoming query, each token having a predetermined length and overlapping a previous token by including one or more characters from the previous token.

4. The computer-implemented method of claim 1 , wherein determining the degree of similarity further comprises computing an average randomized easy signature by performing the steps of:

computing a plurality of randomized easy signatures; and

averaging the plurality of randomized easy signatures.

5. The computer-implemented method of claim 3 , wherein the incoming query comprises a title of the content item.

6. The computer-implemented method of claim 3 , wherein the incoming query comprises a list of keywords corresponding to the content item.

7. The computer-implemented method of claim 3 , wherein the incoming query comprises a body of the content item.

8. The computer-implemented method of claim 3 , wherein the predetermined length of each token is three.

9. A computer-implemented system of selecting a content item from a content item database, the system comprising:

a content item database which stores a plurality of content items;

a server which performs offline processing, the offline processing comprising:

accessing a content item from the content item database;

creating a first set of tokens from the content item;

calculating a first total as a number of tokens in first set of tokens; and

storing the first set of tokens and the first total; and

a client which performs online processing, the online processing comprising:

receiving an incoming query;

creating a second set of tokens from the incoming query;

calculating a second total as a number of tokens in the second set of tokens;

accessing the first set of tokens and the first total corresponding to one of the plurality of content items in the content item database;

determining a number of common tokens based on a minimum of a first count and a second count, the first count being a count of each unique token in the first set of tokens and the second count being a count of the each unique token in the second set of tokens;

computing a randomized easy signature by:

selecting a set of most frequent tokens from the second set of tokens;

computing a second total as a number of tokens in the selected set of most frequent tokens;

randomly selecting a sub-set of tokens from the selected set of most frequent tokens;

determining a number of common tokens based on a minimum of the first count and a third count, the third count being a count of the unique token in the randomly selected sub-set of tokens; and

determining the randomized easy signature as a ratio of the number of common tokens and a sum of the first total and the second total; and

designating the content item in the content item database as matching the incoming query when the easy signature exceeds a predetermined threshold.

10. The computer-implemented system of claim 9 , wherein the incoming query comprises at least one of a search string and a user query.

11. The computer-implemented system of claim 9 , wherein the content item comprises at least one of an e-mail, an instant message, a chat message, a text messages, a SMS message, a paging communication, a blog post, and a news item.

12. The computer-implemented system of claim 9 , wherein creating a first set of tokens comprises:

processing the content item by changing an upper-case letter into a lower-case letter and removing a space; and

creating the first set of tokens from the processed content item, each token having a predetermined length and overlapping a previous token by including one or more characters from the previous token.

13. A computer program product comprising executable instructions tangibly embodied in a non-transitory computer-readable medium which, when executed by at least one processor, perform a method of selecting a content item, the method comprising:

accessing an incoming query from a memory device;

creating a first set of tokens from the incoming query;

computing a first total as a number of tokens in the first set of tokens;

accessing a second set of tokens, corresponding to the content item stored in the content item database;

determining a degree of similarity by:

determining a minimum of a first count and a second count, the first count being a count of a unique token in the first set of tokens and the second count being a count of the unique token in the second set of tokens; and

computing a randomized easy signature by:

selecting a set of most frequent tokens from the second set of tokens;

computing a second total as a number of tokens in the selected set of most frequent tokens;

randomly selecting a sub-set of tokens from the selected set of most frequent tokens;

determining a number of common tokens based on a minimum of the first count and a third count, the third count being a count of the unique token in the randomly selected sub-set of tokens; and

determining the randomized easy signature as a ratio of the number of common tokens and a sum of the first total and the second total; and

identifying the content item as matching the incoming query if the degree of similarity exceeds a predetermined threshold.

14. The computer program product of claim 13 , wherein the incoming query comprises at least one of a search string and a user query.

15. The computer program product of claim 13 , wherein the content item comprises at least one of an e-mail, an instant message, a chat message, a text messages, a SMS message, a paging communication, a blog post, and a news item.

16. The computer program product of claim 13 , wherein the method performed by the at least one processor further comprises:

computing an average randomized easy signature by performing the following:

computing a plurality of randomized easy signatures; and

averaging the plurality of randomized easy signatures.

Assignments (7)
PATENT SECURITY AGREEMENT (FIRST LIEN) Recorded Sep 29, 2022
From: YAHOO ASSETS LLC
To: ROYAL BANK OF CANADA, AS COLLATERAL AGENT
Reel/Frame 061571/0773 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Dec 16, 2021
From: YAHOO AD TECH LLC (FORMERLY VERIZON MEDIA INC.)
To: YAHOO ASSETS LLC
Reel/Frame 058982/0282 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Oct 26, 2020
From: OATH INC.
To: VERIZON MEDIA INC.
Reel/Frame 054258/0635 →
CHANGE OF NAME Recorded Aug 24, 2017
From: AOL INC.
To: OATH INC.
Reel/Frame 043672/0369 →
RELEASE OF SECURITY INTEREST IN PATENT RIGHTS -RELEASE OF 030936/0011 Recorded Jul 1, 2015
From: JPMORGAN CHASE BANK, N.A.
To: AOL ADVERTISING INC.; AOL INC.; BUYSIGHT, INC.; MAPQUEST, INC.; PICTELA, INC.
Reel/Frame 036042/0053 →
SECURITY AGREEMENT Recorded Aug 2, 2013
From: AOL INC.; AOL ADVERTISING INC.; BUYSIGHT, INC.; MAPQUEST, INC.; PICTELA, INC.
To: JPMORGAN CHASE BANK, N.A., AS ADMINISTRATIVE AGENT
Reel/Frame 030936/0011 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jul 11, 2011
From: CHANDRASEKHARAPPA, SANTHOSH BARAMASAGARA; EKAMBARAM, SIVAKUMAR; SOHONEY, SAURABH; NIGAM, RAKESH
To: AOL INC.
Reel/Frame 026571/0855 →