Building a social graph using sharing activity of users of the open web by creating an edge representing a category type

• US 9,146,998 B2
• Filed: 03/10/2015
• Issued: 09/29/2015
• Est. Priority Date: 06/16/2011
• Status: Active Grant

• Current Assignee: R1 Demand, LLC
• Original Assignee: Radiumone (Tremor International Ltd.)
• Inventors: Vaynblat, Dimitri, Chahal, Gurbaksh
• Primary Examiner(s): Barry, Lance L
• Application Number:
  US14/644,117
• Publication Number:
  US 20150186523A1
• Time in Patent Office: 203 Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/22 Indexing; Data structures therefor; Storage structures
• CPC Class Codes: G06F 16/23 Updating
• CPC Class Codes: G06F 16/24575 using context
• CPC Class Codes: G06F 16/2465 Query processing support for facilitating data mining operations in structured databases
• CPC Class Codes: G06F 16/248 Presentation of query results
• CPC Class Codes: G06F 16/25 Integrating or interfacing systems involving database management systems
• CPC Class Codes: G06F 16/285 Clustering or classification
• CPC Class Codes: G06F 16/35 Clustering; Classification
• CPC Class Codes: G06F 16/9024 Graphs; Linked lists G06F16/9027 takes precedence
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques
• CPC Class Codes: G06F 16/955 using information identifiers, e.g. uniform resource locators [URL]
• CPC Class Codes: G06Q 30/0201 Market modelling; Market analysis; Collecting market data
• CPC Class Codes: G06Q 30/0241 Advertisements
• CPC Class Codes: G06Q 30/0244 Optimization
• CPC Class Codes: G06Q 30/0255 based on user history
• CPC Class Codes: G06Q 30/0261 based on user location
• CPC Class Codes: G06Q 30/0269 based on user profile or attribute
• CPC Class Codes: G06Q 30/0271 Personalized advertisement
• CPC Class Codes: G06Q 30/0273 Determination of fees for advertising
• CPC Class Codes: G06Q 30/0275 Auctions
• CPC Class Codes: G06Q 30/0277 : Online advertisement
• CPC Class Codes: G06Q 30/0641 : Shopping interfaces
• CPC Class Codes: G06Q 50/01 : Social networking
• CPC Class Codes: H04L 12/1813 : for computer conferences, e.g. chat rooms instant messaging H04L51/04; protocols for multimedia communication H04L65/1101; arrangements for multi-party communication H04L65/403; telephonic conference arrangements H04M3/56; television conference systems H04N7/15
• CPC Class Codes: H04L 41/12 : Discovery or management of network topologies
• CPC Class Codes: H04L 43/045 : for graphical visualisation of monitoring data
• CPC Class Codes: H04L 43/06 : Generation of reports
• CPC Class Codes: H04L 51/04 : Real-time or near real-time messaging, e.g. instant messaging [IM]
• CPC Class Codes: H04L 51/046 : Interoperability with other network applications or services
• CPC Class Codes: H04L 51/10 : Multimedia information
• CPC Class Codes: H04L 51/52 : for supporting social networking services
• CPC Class Codes: H04L 51/56 : Unified messaging, e.g. interactions between e-mail, instant messaging or converged IP messaging [CPM]
• 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 67/51 : Discovery or management thereof, e.g. service location protocol [SLP] or web services
• CPC Class Codes: H04L 67/535 : Tracking the activity of the user network monitoring arrangements H04L43/00; recording of computer activity G06F11/34
• CPC Class Codes: H04L 67/565 : Conversion or adaptation of application format or content adding application control or application functional data H04L67/561
• CPC Class Codes: H04W 4/12 : Messaging; Mailboxes; Announcements

Abstract

A social graph is built which includes interactions, sharing activity, and connections between the users of the open Web and can be used to improve ad targeting and content personalization. Sharing activity between two users will affect ads or content that both users will be presented while surfing the Web. This sharing activity includes sending of links, sending of videos, sending of files, cutting and pasting of content, sending text messages, and sending of e-mails. For example, the sharing activity can include receiving first activity information for a sender of a message to a recipient by a collection resource at a Web site, the collection resource adding a link to the message, and receiving second activity information when the recipient accesses the link. Building of the social graph can include creating an edge in the social graph that is representative of a particular category type.

Claims

1. A method comprising:

receiving first activity information for a sender of a message sent to at least one recipient by a collection resource at a Web site, wherein the message comprises text associated with the Web site, the collection resource adds a first link to the message, and no personally identifiable information of the sender is collected in collecting the first activity information;

storing the first activity information at a storage server;

receiving second activity information when a first recipient accesses the first link sent by the sender corresponding to the first activity information stored at the storage server, wherein no personally identifiable information of the first recipient is collected in the second activity information;

using at least one processor, using the first activity information to identify a first node in a social graph as being representative of the sender;

using the second activity information to identify a second node in the social graph as being representative of the first recipient;

determining a category for the first link as a first category type; and

in the social graph, creating a first edge between the first and second nodes, wherein the first edge is representative of the first category type.

2. The method of claim 1 wherein the text is copied from the Web site.

3. The method of claim 2 wherein the copied text is pasted into the message.

4. The method of claim 1 wherein the message comprises text and an image.

5. The method of claim 1 wherein the message comprises an image.

6. The method of claim 1 wherein the message comprises a video.

7. The method of claim 1 wherein the first recipient is represented as a node in the social graph.

8. The method of claim 1 further comprising:

generating the first link based on the message, wherein the first link is associated with the text and the first link comprises a reference to information accessible over the Internet.

9. The method of claim 8 wherein the first link comprises a reference to a first information accessible over the Internet, different from a second link to the Web site accessed by the sender.

10. The method of claim 1 wherein the first link is generated in response to the message.

11. The method of claim 1 wherein the first link is uniquely associated with the sender.

12. The method of claim 1 further comprising:

storing in the social graph the second activity information.

13. The method of claim 1 wherein the first activity information stored in the social graph comprises associating the sender with the first activity information.

14. The method of claim 1 wherein the first edge in the social graph comprises a weighted edge.

15. The method of claim 1 wherein the first link comprises a shortened uniform resource locator.

16. The method of claim 1 further comprising:

receiving third activity information when a second recipient accesses the first link sent by the sender corresponding to the first activity information stored at the storage server, wherein no personally identifiable information of the second recipient is collected in the third activity information; and

using the third activity information to identify a third node in the social graph as being representative of the second recipient.

17. The method of claim 1 wherein the using the first activity information to identify a first node in a social graph as being representative of the sender comprises:

extracting a user identifier from a cookie received with the first activity data; and

if a match for the user identifier is not found in the social graph, performing a probabilistic fingerprinting approach using attributes comprising at least one of device identifiers;

IP addresses;

operating systems;

browsers types;

browser versions;

or user navigational, geo-temporal, and behavioral patterns.

18. The method of claim 1 wherein the using the first activity information to identify a first node in a social graph as being representative of the sender comprises:

extracting a user identifier from the first activity data; and

if a match for the user identifier is not identified in the social graph, performing a deterministic fingerprinting approach using attributes comprising at least one of device identifiers;

IP addresses;

operating systems;

browsers types;

browser versions;

or user navigational, geo-temporal, and behavioral patterns.

19. The method of claim 1 wherein the using the first activity information to identify a first node in a social graph as being representative of the sender comprises:

extracting a user identifier from the first activity data; and

if a match for the user identifier is not found in the social graph, attempting to match a nonmobile Web browser identifier to a mobile Web browser identifier.

20. The method of claim 1 wherein the using the first activity information to identify a first node in a social graph as being representative of the sender comprises:

extracting a user identifier from the first activity data; and

if a match for the user identifier is not found in the social graph, attempting to match a plurality of mobile device identifiers in a selected geo-vicinity and selected time interval.