Systems And Methods For Determining User Attribute Values By Mining User Network Data And Information

• US 20130218965A1
• Filed: 08/17/2012
• Published: 08/22/2013
• Est. Priority Date: 08/19/2011
• Status: Active Grant

• Current Assignee: Board of Regents of the University of Texas System (University of Texas System)
• Original Assignee: Board of Regents of the University of Texas System (University of Texas System)
• Inventors: Khan, Latifur Rahman, Thuraisingham, Bhavani Marienne, Abrol, Satyen, Khadilkar, Vaibhav
• Granted Patent: US 8,965,974 B2
• Time in Patent Office: Days
• US Class Current: 709/204
• CPC Class Codes: H04L 67/306 User profiles
• CPC Class Codes: H04L 67/52 specially adapted for the location of the user terminal
• CPC Class Codes: H04L 67/535 Tracking the activity of the user network monitoring arrangements H04L43/00; recording of computer activity G06F11/34

Abstract

Systems and methods for determining one or more attributes and their associated values for a user, by mining the user'"'"'s social network profiles. The systems and methods determine if the value of an attribute of interest for a user is specified on one or more social networking websites. If so, the systems and methods set the attribute value for the user to the specified attribute value. If not, the systems and methods retrieve, from the social networking websites, attribute values for the attribute of interest for friends of the user to form a group of possible attribute values for the user. The method, selects a value from the group of possible attribute values, and then sets the selected value as the attribute value for the user.

Claims

1. A method in a data processing system for determining a value of an attribute of a user, comprising:

by a processor in the data processing system, determining if a value of an attribute of interest for a user is specified on one or more social networking websites;

responsive to a determination that the value of an attribute of the user is not specified., obtaining, from the one or more social networking websites, attribute values for the attribute of interest for friends of the user to form a group of possible attribute values for the user;

selecting a value from the group of possible attribute values; and

setting the selected value as the attribute value for the user.

2. The method of claim 1, further comprising:

responsive to a determination that the value of an attribute of the user is specified, retrieving and setting the specified value as the attribute value for the user.

3. The method of claim 1, wherein the attribute comprises one or more of a location, age, age group, race, ethnicity, threat, languages spoken, religion, economic status, education level, gender, hobby, or interest.

4. The method of claim 1, wherein determining if a value of an attribute of a user is specified on one or more social networking websites further comprises:

obtaining an identifier of the user from a social network profile of the user; and

obtaining the attribute value for the user, if specified, using the identifier of the user.

5. The method of claim 1, wherein retrieving attribute values corresponding to the attribute of interest for friends of the user to form a group of possible attribute values for the user comprises:

obtaining a user identifier for each of the friends of the user from their social network profiles; and

obtaining the attribute values for the friends, if specified on the one or more social networking websites, using the user identifier of each friend.

6. The method of claim 1, wherein selecting a value from the group of possible attribute values comprises:

selecting the value having a maximum frequency among the friends of the user.

7. The method of claim 1, wherein selecting a value from the group of possible attribute values comprises:

determining a set of closest friends of the user;

obtaining a value for the attribute of interest for each friend in the set of closest friends;

aggregating and determining a weight for each obtained value; and

selecting a value from the obtained values for the set of closest friends having a highest weighted, score.

8. The method of claim 7, wherein determining a set of closest friends of the user further comprises:

determining a number of friends in common between the user and each friend of the user; and

determining the set of closest friends based on the number of friends in common between the user and each friend.

9. The method of claim 8, further comprising:

determining a friend of the user is a spammer if a difference between a number of users the spammer follows and a number of users following the spammer is equal to or greater than a threshold; and

responsive to determining the friend of the user is a spammer, setting the number of friends in common between the user and the friend to 0.

10. The method of claim 1, wherein selecting a value from the group of possible attribute values further comprises:

determining a set of closest friends of the user;

obtaining a value for the attribute of interest for each friend in the set of closest friends, wherein the obtained, values comprise an array of values, and wherein each value in the array is associated with a probability score; and

selecting a value from the array of values having a highest calculated score among the set of closest friends.

11. The method of claim 10, wherein the attribute is a location, and further comprising:

combining two concepts, wherein each concept represents a location;

assigning one or more weights to each concept; and

calculating a weight score for each concept based on the weights of each concept;

wherein the combining, assigning, and calculating steps are repeated until a determination is made that the combined concepts have a weight score greater than a location confidence threshold (LCT).

12. The method according to claim 11, wherein the combined concepts represent a potential location vector.

13. The method of claim 1, wherein the value of the attribute of interest for the user is specified on a publicly available profile of the one or more social networking websites.

14. A method in a data processing system for determining a location of a user, comprising:

extracting text from messages provided by a user on a social networking website, wherein the messages include one or more location concepts;

removing words unrelated to geographical locations from the text;

assigning a weight to each location concept based on the occurrence of the location concept in the text, wherein specific location concepts are assigned a greater weight compared to general location concepts;

responsive to determining a correlation between a specific location concept and a general location concept, adding the weight of the general location concept to the specific location concept;

reordering the location concepts in descending order of weights;

assigning a probability score (S) to each location concept (C) based on its individual weight; and

based on the probability scores, assigning a location concept to the user.

15. The method of claim 14, wherein the location concept comprises a specified geographical location and is of the format {City}/{State}/{Country}.

16. The method of claim 15, wherein a value of one or more of the City, the State, or the Country is null.

17. An apparatus for determining a value of an attribute of a user, comprising:

a bus;

a storage device connected to the bus, wherein the storage device contains computer usable code; and

a processing unit connected to the bus, wherein the processing unit executes the computer usable code to determine if a value of an attribute of interest for a user is specified on one or more social, networking websites;

obtain, from the social networking websites, attribute values for the attribute of interest for friends of the user to form a group of possible attribute values for the user in response to a determination that the value of an attribute of the user is not specified;

select a value from the group of possible attribute values; and

set the selected value as the attribute value for the user.

18. The apparatus of claim 17, wherein the selection of the value from the group of possible attribute values further comprises a selection of the attribute value having a maximum frequency among the friends of the user.

19. The apparatus of claim 17, wherein the selection of the value from the group of possible attribute values further comprises a determination of a number of friends in common between the user and each friend of the user;

a determination of a set of closest friends based on the number of friends in common between the user and each friend;

obtaining a value for the attribute of interest for each friend in the set of closest friends;

aggregating and determining a weight for each obtained value; and

a selection of a value from the obtained values having a highest weighted score among the set of closest friends.

20. The apparatus of claim 17, wherein the selection of the value from the group of possible attribute values further comprises a determination of a number of friends in common between the user and each friend of the user;

a determination of a set of closest friends based on the number of friends in common between the user and each friend;

obtaining a value for the attribute of interest for each friend in the set of closest friends, wherein the obtained, values comprise an array of values, and wherein each value in the array is associated with a probability score; and

a selection of a value from the array of values having a highest calculated score among the set of closest friends.