Context based online advertising

• US 8,655,667 B2
• Filed: 11/19/2012
• Issued: 02/18/2014
• Est. Priority Date: 08/18/2008
• Status: Active Grant

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Corporation
• Inventors: Chandrasekar, Raman, Chang, Eric I-Chao, Bai, Tian, Tsang, Michael
• Primary Examiner(s): AZAD, ABUL K
• Application Number:
  US13/680,819
• Publication Number:
  US 20130151258A1
• Time in Patent Office: 456 Days
• Field of Search: 704/270, 704/270.1, 704/272, 704/276, 704/257
• US Class Current: 704/276
• CPC Class Codes: G06F 40/237 Lexical tools
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising

Abstract

A software and/or hardware facility for inferring user context and delivering advertisements, such as coupons, using natural language and/or sentiment analysis is disclosed. The facility may infer context information based on a user'"'"'s emotional state, attitude, needs, or intent from the user'"'"'s interaction with or through a mobile device. The facility may then determine whether it is appropriate to deliver an advertisement to the user and select an advertisement for delivery. The facility may also determine an appropriate expiration time and/or discount amount for the advertisement.

Claims

1. One or more processor-readable storage devices containing instructions, that when executed by at least one processor, perform acts comprising:

determining a mobile device characteristic based on a mobile device context of a mobile device;

determining a user characteristic that includes sentiment information based at least in part on a user interaction with the mobile device, the sentiment information including a mood, emotional state or attitude of a user of the mobile device;

determining an advertisement based at least in part on the determined mobile device characteristic and the determined user characteristic;

determining a time, based at least in part on the sentiment information, at which the user is expected to desire, need, and/or be predisposed to have a positive response to the advertisement; and

selectively delivering the advertisement at the time to the mobile device.

2. The one or more processor-readable storage devices of claim 1, the acts further comprising:

extracting natural language information from the user interaction with the mobile device; and

extracting the sentiment information from the natural language information.

3. The one or more processor-readable storage devices of claim 1, wherein determining the user characteristic includes:

receiving user speech data; and

extracting the sentiment information from the received user speech data.

4. The one or more processor-readable storage devices of claim 1, wherein determining the advertisement includes selecting the advertisement from multiple advertisements based at least in part on the determined mobile device characteristic and the determined user characteristic.

5. The one or more processor-readable storage devices of claim 1, wherein selectively delivering the advertisement includes determining at least one of an advertisement expiration time or an advertisement discount amount based at least in part on the determined mobile device characteristic and the determined user characteristic.

6. The one or more processor-readable storage devices of claim 1, wherein determining the mobile device characteristic further includes determining ancillary information including at least one of a location of the mobile device, a speed of the mobile device, or a time at the mobile device, wherein the mobile device context is further based on the determined ancillary information.

7. The one or more processor-readable storage devices of claim 1, wherein determining the user characteristic further includes determining a user context based at least in part on determining environmental information including at least one of ambient temperature information, body temperature information, heart rate information, humidity information, pressure information, weather information, traffic condition information, or information relating to proximity of the mobile device to other mobile devices.

8. The one or more processor-readable storage devices of claim 1, wherein selectively delivering the advertisement is further based on an advertisement effectiveness characteristic.

9. The one or more processor-readable storage devices of claim 8, wherein the advertisement effectiveness characteristic includes at least one of a redemption rate, response rate, discount amount, community-based feedback, advertiser popularity, product popularity, or service popularity of the selectively delivered advertisement.

10. The one or more processor-readable storage devices of claim 8, the acts further comprising:

receiving user feedback including a response from the user of the mobile device corresponding to the selectively delivered advertisement;

determining the advertisement effectiveness characteristic based at least in part on the received user feedback; and

selectively delivering another advertisement based at least in part on the determined advertisement effectiveness.

11. The one or more processor-readable storage devices of claim 1, the acts further comprising estimating a demand for at least one of a product or service based on the selectively delivered advertisement.

12. A method comprising:

determining a mobile device characteristic based on a mobile device context of a mobile device;

determining a user characteristic that includes sentiment information based at least in part on user interaction with the mobile device;

determining an advertisement based at least in part on the determined mobile device characteristic and the determined user characteristic;

determining a time, based at least in part on the sentiment information, at which a user of the mobile device is expected to have a positive response to the advertisement; and

selectively delivering the advertisement at the time to the mobile device and to a client device of the user that differs from the mobile device.

13. The method of claim 12, wherein determining the user characteristic includes:

receiving user speech data; and

extracting the sentiment information from the received user speech data.

14. The method of claim 12, wherein the sentiment information includes a mood, emotional state or attitude of the user of the mobile device.

15. The method of claim 12, wherein determining the user characteristic further includes determining a user context based at least in part on determining environmental information including at least one of ambient temperature information, body temperature information, heart rate information, humidity information, pressure information, weather information, traffic condition information, or information relating to proximity of the mobile device to other mobile devices.

16. The method of claim 12, further comprising determining at least one of an advertisement expiration time or an advertisement discount amount based on the determined mobile device characteristic and the determined user characteristic.

17. A method comprising:

determining a mobile device characteristic based at least in part on a mobile device context of a mobile device;

determining a user characteristic of a user of the mobile device based at least in part on user interaction with the mobile device that includes at least one of natural language information or sentiment information, the natural language information including at least one of speech transmitted or speech received by the mobile device during a telephonic conversation; and

selectively delivering an advertisement to the mobile device and to a client device of the user that differs from the mobile device based at least in part on the determined mobile device characteristic and the determined user characteristic.

18. The method of claim 17, further comprising:

receiving user speech data; and

extracting at least one of the natural language information or the sentiment information from the received user speech data.

19. The method of claim 17, further comprising:

selecting the advertisement from multiple advertisements based on the determined mobile device characteristic and the determined user characteristic;

determining at least one of an advertisement expiration time or an advertisement discount amount based on the determined mobile device characteristic and the determined user characteristic; and

selecting a time at which to deliver the selected advertisement.

20. The method of claim 17, further comprising:

receiving user feedback corresponding to the selectively delivered advertisement;

determining the advertisement effectiveness characteristic based on the received user feedback; and

selectively delivering another advertisement based on the determined advertisement effectiveness.