ACTION-AWARE INTENT-BASED BEHAVIOR TARGETING

• US 20120197732A1
• Filed: 01/31/2011
• Published: 08/02/2012
• Est. Priority Date: 01/31/2011
• Status: Abandoned Application

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Corporation
• Inventors: HUANG, JIAYUAN, LI, YING, SHEN, DOU, YAN, JUN, WANG, XIANFANG, LIBORSKI, VALERI
• Application Number:
  US13/017,843
• Publication Number:
  US 20120197732A1
• Time in Patent Office: Days
• US Class Current: 705/14.66
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0269 based on user profile or attribute

Abstract

Methods and computer-storage media having computer-executable instructions embodied thereon that facilitate classifying user intent with respect to an entity using intent-strength scores. A user query indicating a particular entity is received. The user'"'"'s intent with respect to the particular entity is determined by assigning an intent-strength score to the user. The user'"'"'s intent-strength score is determined using intent-strength scores assigned to seed patterns identified for entities in a category, as well as the received user query. In embodiments, a user'"'"'s intent-strength score may be updated based on a subsequent query, or may be changed according to a function. A list of users having particular intent-strength scores for particular entities may be also be generated.

Claims

1. One or more computer-readable media storing computer-usable instructions that, when used by one or more computing devices, causes the one or more computing devices to perform a method for classifying user intent with respect to at least one entity, the method comprising:

identifying one or more seed patterns for the at least one entity, wherein the one or more seed patterns comprise one or more terms and a name for the at least one entity;

expanding the one or more identified seed patterns using query log data to identify one or more additional seed patterns for the at least one entity; and

assigning intent-strength scores to the one or more identified seed patterns and the one or more additional seed patterns, wherein the intent-strength scores identify a level of user interest with respect to the at least one entity.

2. The one or more computer-readable media of claim 1, wherein the method further comprises:

assigning a corresponding intent-strength score with each of one or more users, the intent-strength score indicating each of the one or more user'"'"'s classified user intent, wherein the corresponding intent-strength score is based on one or more user queries entered by each of the one or more users and the intent strength-scores assigned to the one or more identified seed patterns and the one or more additional seed patterns.

3. The one or more computer-readable media of claim 2, wherein associating a corresponding intent-strength score with each of one or more users comprises:

updating the corresponding intent-strength score assigned to each of the one or more users based on one or more subsequent queries entered by the one or more users and the intent-strength scores assigned to the one or more identified seed patterns and the one or more additional seed patterns.

4. The one or more computer-readable media of claim 2, wherein associating a corresponding intent-strength score with each of one or more users comprises:

changing the corresponding intent-strength score according to a function, wherein the function varies according to one or more variables, the one or more variables comprising time, product characteristics, and user characteristics.

5. The one or more computer-readable media of claim 2, wherein the method further comprises:

presenting at least one behavior-targeted display advertisement to the one or more users, the behavior-targeted display advertisement associated with the entity, wherein said presenting is based on each of the one or more user'"'"'s classified user intent with respect to the entity.

6. The one or more computer-readable media of claim 5, wherein the method further comprises:

receiving an indication that at least one of the one or more users is accessing an internet browser of a computing device; and

presenting the at least one behavior-targeted display advertisement to the at least one of the one or more users using the internet browser.

7. The one or more computer-readable media of claim 6, wherein receiving an indication that the at least one of the one or more users is accessing an internet browser of a computing device comprises one or more of monitoring the at least one user'"'"'s user ID and monitoring the at least one user'"'"'s machine ID.

8. The one or more computer-readable media of claim 1, wherein identifying one or more seed patterns for at least one entity comprises manually defining one or more seed patterns for the at least one entity.

9. The one or more computer-readable media of claim 1, wherein expanding the one or more identified seed patterns using query log data from one or more users comprises utilizing random walk to expand the one or more identified seed patterns.

10. The one or more computer-readable media of claim 1, wherein assigning intent-strength scores to the one or more identified seed patterns and the additional one or more seed patterns comprises:

utilizing a machine-learning model to associate intent-strength scores with one or more of the one or more identified seed patterns and the one or more additional seed patterns.

11. One or more computer-readable media storing computer-usable instructions that, when used by one or more computing devices, causes the one or more computing devices to perform a method for classifying user intent with respect to at least one entity, the method comprising:

assigning intent-strength scores to each of one or more seed patterns, wherein the one or more seed patterns were identified for the at least one entity, wherein an intent-strength score describes a user'"'"'s level of interest related to the at least one entity; and

assigning corresponding intent-strength scores to each of a first set of one or more users by correlating on one or more queries entered by the first set of one or more users with the intent-strength scores assigned to the one or more seed patterns.

12. The one or more computer-readable media of claim 11, wherein the method further comprises:

generating a user interface for selecting a group of users from the first set of one or more users for presenting behavior-targeted advertisements to, the selected group of users having particular corresponding intent-strength scores, the user interface comprising;

(1) a first display area for receiving an indication of a category selection, the category selection indicating a type of entity; and

(2) a second display area for receiving an indication of a desired level of user intent related to the selected category, wherein the level of user intent is specified with intent-strength scores.

13. The one or more computer-readable media of claim 11, wherein assigning intent-strength scores to each of one or more seed patterns comprises:

expanding the one or more identified seed patterns to identify one or more additional seed patterns using query log data from a second set of one or more users; and

assigning intent-strength scores to each of the one or more additional seed patterns.

14. The one or more computer-readable media of claim 11, wherein assigning corresponding intent-strength scores to a first set of one or more users further comprises:

updating the corresponding intent-strength scores assigned to the first set of one or more users based on one or more subsequent queries entered by the first set of one or more users and the intent-strength scores assigned to the one or more seed patterns.

15. The one or more computer-readable media of claim 11, wherein assigning corresponding intent-strength scores to a first set of one or more users further comprises:

changing the corresponding intent-strength scores according to a function, wherein the function varies according to one or more variables, the one or more variables comprising time, product characteristics, and user characteristics.

17. The one or more computer-readable media of claim 15, wherein the method further comprises:

presenting at least one behavior-targeted display advertisement to the user, the at least one behavior-targeted display advertisement based on the user'"'"'s classified user intent.

18. The one or more computer-readable media of claim 15, wherein assigning intent-strength scores to each of one or more seed patterns comprises:

expanding the one or more identified seed patterns to identify one or more additional seed patterns using query log data from a plurality of users; and

assigning intent-strength scores to the one or more identified seed patterns and the one or more additional seed patterns.

19. The one or more computer-readable media of claim 15, wherein the method further comprises:

updating the user'"'"'s classified intent with respect to the at least one entity based on one or more subsequent indications of user queries submitted by the user and the intent-strength scores assigned to the one or more seed patterns.

20. The one or more computer-readable media of claim 15, wherein classifying the user'"'"'s intent with respect to the at least one entity comprises:

changing the corresponding intent-strength score assigned to the user according to a function, wherein the function varies according to one or more variables, the one or more variables comprising time, product characteristics, and user characteristics; and

updating the user'"'"'s intent with respect to the at least one entity based on changing the corresponding intent-strength score according to the function.

16. One or more computer-readable media storing computer-usable instructions that, when used by one or more computing devices, causes the one or more computing devices to perform a method for determining a user'"'"'s classified user intent with respect to at least one entity, the method comprising:

receiving an indication of a user query submitted by the user; and

classifying the user'"'"'s intent with respect to the at least one entity, the classified user intent having an assigned intent-strength score, wherein the user'"'"'s assigned intent-strength score is determined according to the following;

(1) assigning intent-strength scores to each of one or more seed patterns, wherein the one or more seed patterns were identified for the at least one entity; and

(2) assigning a corresponding intent-strength score to the user that indicates the user'"'"'s classified user intent, wherein the corresponding intent-strength score is based on the indication of a user query submitted by the user and the intent-strength scores assigned to each of the one or more seed patterns.