System and method for spam identification

• US 20060248072A1
• Filed: 04/29/2005
• Published: 11/02/2006
• Est. Priority Date: 04/29/2005
• Status: Active Grant

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Corporation
• Inventors: Watson, Eric B., Brewer, Brett D.
• Granted Patent: US 7,660,792 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/904 Browsing; Visualisation therefor for navigating the web G06F16/954; browsing optimisation for the web G06F16/957
• CPC Class Codes: G06F 16/954 Navigation, e.g. using categorised browsing

Abstract

A system and method are provided for improving a user search experience by identifying spam results in a result set produced in response to a query. The system may include a user interface spam feedback mechanism for allowing a user to indicate that a given result is spam. The system may additionally include an automated spam identification mechanism for implementing automated techniques on the given result to determine whether the given result is spam. The system may further include a merging component for merging the determinations of the user interface spam feedback mechanism and the automated spam identification mechanism for deriving an indicator of the likelihood that a given result is spam.

Claims

1. A method for improving a user search experience by identifying any spam results in a result set produced in response to a query, the method comprising:

receiving user feedback indicating whether a given result is spam;

implementing automated spam identification techniques on the given result; and

merging data obtained from the user feedback and the automated spam identification techniques to obtain an indicator for the given result, the indicator providing a likelihood that the given result is spam.

2. The method of claim 1, further comprising analyzing the user feedback to determine if the user feedback is spam.

3. The method of claim 2, wherein analyzing the user feedback comprises determining a source of the feedback and determining whether the feedback originates with unique users.

4. The method of claim 1, further comprising analyzing the user feedback for the given result across multiple queries.

5. The method of claim 1, wherein the automated spam identification techniques comprise determining a query independent rank of the given result.

6. The method of claim 1, wherein the automated spam identification techniques comprise a monetization analysis technique that determines keyword monetization value.

7. The method of claim 1, wherein the automated spam identification techniques comprise a popularity analysis technique for determining a popularity of the given result based on user access.

8. The method of claim 1, further comprising storing the given result and the indicator in an index in order so that a ranking mechanism accesses the indicator when the given result is produced in response to any future query.

9. The method of claim 1, further comprising implementing automated spam identification techniques in the absence of user feedback.

10. A method for improving a user search experience by identifying any spam results in a result set produced in response to a query, the method comprising:

providing a user interface spam feedback mechanism for allowing a user to indicate that a given result is spam; and

implementing the received feedback to alter a future ranking of the given result based on the user feedback.

11. The method of claim 10, further comprising determining whether user feedback is spam.

12. The method of claim 11, wherein determining whether user feedback is spam comprises determining a source of the feedback and determining whether the feedback originates with unique users.

13. The method of claim 10, further comprising analyzing the user feedback for the given result across multiple queries.

14. The method of claim 10, further comprising implementing automated spam identification techniques on the given result and merging the automated spam identification determination with the user feedback to derive a spam indicator.

15. The method of claim 14, wherein the automated spam identification techniques comprise determining a query independent rank of the given result.

16. The method of claim 14, wherein the automated spam identification techniques comprise a monetization analysis technique that determines keyword monetization value.

17. The method of claim 14, wherein the automated spam identification techniques comprise a popularity analysis technique for determining a popularity of the given result based on user access.

18. The method of claim 14, further comprising storing the given result and the spam indicator in an index in order so that a ranking mechanism accesses the indicator when the given result is produced in response to any future query.

19. A system for improving a user search experience by identifying spam results in a result set produced in response to a query, the system comprising:

a user interface spam feedback mechanism for allowing a user to indicate that a given result is spam;

an automated spam identification mechanism for implementing automated techniques on the given result to determine whether the given result is spam; and

a merging component for merging the determinations of the user interface spam feedback mechanism and the automated spam identification mechanism for deriving an indicator of the likelihood that a given result is spam.

20. The system of claim 19, further comprising an indexing mechanism for storing the given result and the spam indicator in an index in order so that a ranking mechanism accesses the spam indicator when the given result is produced in response to any future query.