Reverse ID class inference via auto-grouping

• US 20070133385A1
• Filed: 12/14/2005
• Published: 06/14/2007
• Est. Priority Date: 12/14/2005
• Status: Abandoned Application

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Corporation
• Inventors: Padmanabhan, Venkata, Hoek, Hank
• Application Number:
  US11/304,843
• Publication Number:
  US 20070133385A1
• Time in Patent Office: Days
• US Class Current: 370/201
• CPC Class Codes: G06F 16/9537 Spatial or temporal dependent retrieval, e.g. spatiotemporal queries
• CPC Class Codes: H04L 61/35 involving non-standard use of addresses for implementing network functionalities, e.g. coding subscription information within the address or functional addressing, i.e. assigning an address to a function

Abstract

Class information is leveraged to facilitate in grouping identifications (ID) to allow ID range-to-class mapping information to be determined. ID range-to-class inference techniques are employed to determine similarities of IDs associated with a class, creating ID range-to-class mapping. Identifications can include Internet Protocol (IP) addressing, telephone numbers, and other sequenceable forms of identification for users and/or computing devices. Classes can include user location, age, income, gender, language, and/or other classifications. Thus, IP address ranges, for example, can be mapped to user geographic locations using an inference technique, specifically a “GeoInference” technique. The inference techniques quickly detect IP proxy usage and identify and eliminate outliers within a given IP range, substantially increasing the accuracy of user location data. Complementary data sources can be employed to facilitate in increasing data accuracy.

Claims

1. A system that facilitates a identification (ID) range-to-class inference, comprising:

a receiving component that receives class and associated identification (ID) information; and

an inference component that infers at least one ID range-to-class grouping based on, at least in part, a distribution of a user class associated with the identification information.

2. The system of claim 1, the inference component employs an isLike function to facilitate in determining the ID range-to-class grouping.

3. The system of claim 1, the identification (ID) comprising an Internet Protocol (IP) address and/or a telephone number.

4. The system of claim 1, the class comprising geographic location of a user, age of a user, income of a user, gender of a user, and/or language of a user.

5. The system of claim 1 further comprising:

a pre-filtering component that sorts and/or filters the class and associated identification (ID) information from the receiving component and provides it to the inference component.

6. The system of claim 1 further comprising:

an analysis component that determines metrics associated with the ID range-to-class grouping.

7. The system of claim 1 further comprising:

a data combining component that combines ID range-to-class groupings with complementary ID range-to-class mapping data to facilitate in providing hybrid mapping data.

8. The system of claim 1, the class and associated identification (ID) information comprising Internet web log information.

9. An advertising mechanism that employs the system of claim 1 to facilitate in targeting advertisements to users.

20. A device employing the system of claim 1 comprising at least one selected from the group consisting of a computer, a server, and a handheld electronic device.

10. A method for facilitating identification (ID) range-to-class inference, comprising:

obtaining data correlating identification (ID) with an independent source of information relating to a user class;

sorting the data based on the identification (ID); and

applying an inference to construct at least one ID range-to-class grouping of similar class distributions.

11. The method of claim 10 further comprising:

employing an isLike function to facilitate in determining the ID range-to-class grouping.

12. The method of claim 10 further comprising:

utilizing an Internet Protocol (IP) addressing scheme as the identification (ID) to facilitate in determining an ID range-to-class grouping.

13. The method of claim 12 further comprising:

joining IP'"'"'s that are similar in a sequence of octets of an IP address to form candidate groupings; and

evaluating the candidate groupings utilizing an isLike function to join similar candidate groupings.

14. The method of claim 10 further comprising:

employing geographic location of a user as the user class to facilitate in determining an ID range-to-class grouping.

15. The method of claim 10, the data comprising Internet web log data.

16. The method of claim 10 further comprising:

analyzing an ID range-to-class grouping to determine metrics associated with the grouping.

17. The method of claim 10 further comprising:

obtaining reverse-ID mapping data from a complementary data source; and

combining at least one ID range-to-class grouping with the complementary reverse-ID mapping data to construct hybrid reverse-ID mapping data.

19. A device employing the method of claim 10 comprising at least one selected from the group consisting of a computer, a server, and a handheld electronic device.

18. A system that facilitates identification (ID)-to-class range inference, comprising:

means for receiving class and associated identification (ID) information; and

means for inferring at least one ID range-to-class grouping based on, at least in part, a distribution of a user class associated with the identification information.