CONTEXTUALLY SPECIFIC OPPORTUNITY BASED ADVERTISING

• US 20120130806A1
• Filed: 11/18/2010
• Published: 05/24/2012
• Est. Priority Date: 11/18/2010
• Status: Abandoned Application

• Current Assignee: Palo Alto Research Center, Inc. (Xerox Holdings Corp.)
• Original Assignee: Palo Alto Research Center, Inc. (Xerox Holdings Corp.)
• Inventors: Partridge, Kurt E., Begole, James M.A., Chu, Maurice K.
• Application Number:
  US12/949,666
• Publication Number:
  US 20120130806A1
• Time in Patent Office: Days
• US Class Current: 705/14.49
• CPC Class Codes: G06Q 30/0251 Targeted advertisements

Abstract

One embodiment of the present invention provides a system that facilitates contextually specific opportunity-based advertising. During operation, the system collects contextual information associated with a consumer, and determines a current activity and/or a future activity in which the consumer is engaged based on the contextual information. The system then predicts one or more upcoming advertisement opportunities associated with the consumer based on the determined activities, and presents the predicted opportunities to one or more advertisers, thereby allowing the advertisers to determine a bid amount for presenting an advertisement at the predicted opportunities. The system further selects at least one advertisement to present based on one or more of the following: the bid amount, the collected contextual information, an occurrence probability of the predicted advertisement opportunities, content of the advertisement, metadata associated with the advertisement; and presents the advertisement to the consumer.

Claims

1. A computer-implemented method for facilitating contextually specific opportunity-based advertising, the method comprising:

collecting contextual information associated with a consumer;

determining a current activity and/or a future activity in which the consumer is engaged based on the contextual information;

predicting one or more upcoming advertisement opportunities associated with the consumer based on the determined activities;

presenting the predicted opportunities to one or more advertisers, thereby allowing the advertisers to determine a bid amount for presenting an advertisement at the predicted opportunities;

selecting at least one advertisement to present based on one or more of the following;

the bid amount, the collected contextual information, an occurrence probability of the predicted advertisement opportunities, content of the advertisement, metadata associated with the advertisement; and

presenting the advertisement to the consumer.

2. The method of claim 1, further comprising determining the consumer'"'"'s current and/or future receptivity based on the collected contextual information.

3. The method of claim 1, wherein the collected contextual information includes one or more of the following:

time of day;

day of week;

weather condition;

the consumer'"'"'s location;

speed of the consumer'"'"'s motion;

content of the consumer'"'"'s calendar, messages, and emails;

history of the consumer'"'"'s activities;

a statistical model constructed from the history of the consumer'"'"'s activities;

demographic statistics associated with the consumer; and

the consumer'"'"'s previous response to advertisement.

4. The method of claim 1, wherein predicting one or more upcoming advertisement opportunities involves calculating an opportunity score which is a time-varying function of the contextual information.

5. The method of claim 1, further comprising presenting the collected contextual information to the advertisers.

6. The method of claim 1, wherein presenting the advertisement to the consumer involves presenting the advertisement to the consumer in-situ or proactively.

7. The method of claim 1, further comprising calculating a similarity metric between the consumer'"'"'s current situation and a known situation.

8. The method of claim 7, wherein calculating the similarity metric involves at least one of:

comparing contextual information associated with the consumer'"'"'s current situation with contextual information associated with the consumer'"'"'s one or more past situations; and

fitting contextual information associated with the consumer'"'"'s current situation with a statistics model based on historical data associated with the consumer.

9. A computer-readable storage medium storing instructions which when executed by a computer cause the computer to perform a method for facilitating contextually specific opportunity-based advertising, the method comprising:

collecting contextual information associated with a consumer;

determining a current activity and/or a future activity in which the consumer is engaged based on the contextual information;

predicting one or more upcoming advertisement opportunities associated with the consumer based on the determined activities;

presenting the predicted opportunities to one or more advertisers, thereby allowing the advertisers to determine a bid amount for presenting an advertisement at the predicted opportunities;

selecting at least one advertisement to present based on one or more of the following;

the bid amount, the collected contextual information, an occurrence probability of the predicted advertisement opportunities, content of the advertisement, metadata associated with the advertisement; and

presenting the advertisement to the consumer.

10. The computer-readable storage medium of claim 9, wherein the method further comprises determining the consumer'"'"'s current and/or future receptivity based on the collected contextual information.

11. The computer-readable storage medium of claim 9, wherein the collected contextual information includes one or more of the following:

time of day;

day of week;

weather condition;

the consumer'"'"'s location;

speed of the consumer'"'"'s motion;

content of the consumer'"'"'s calendar, messages, and emails;

history of the consumer'"'"'s activities;

a statistical model constructed from the history of the consumer'"'"'s activities;

demographic statistics associated with the consumer; and

the consumer'"'"'s previous response to advertisement.

12. The computer-readable storage medium of claim 9, wherein predicting one or more upcoming advertisement opportunities involves calculating an opportunity score which is a time-varying function of the contextual information.

13. The computer-readable storage medium of claim 9, wherein the method further comprises presenting the collected contextual information to the advertisers.

14. The computer-readable storage medium of claim 9, wherein presenting the advertisement to the consumer involves presenting the advertisement to the consumer in-situ or proactively.

15. The computer-readable storage medium of claim 9, wherein the method further comprises calculating a similarity metric between the consumer'"'"'s current situation and a known situation.

16. The computer-readable storage medium of claim 15, wherein calculating the similarity metric involves at least one of:

comparing contextual information associated with the consumer'"'"'s current situation with contextual information associated with the consumer'"'"'s one or more past situations; and

fitting contextual information associated with the consumer'"'"'s current situation with a statistics model based on historical data associated with the consumer.

17. A computer system that facilitates contextually specific opportunity-based advertising, comprising

a processor;

a memory coupled to the processor;

a collection mechanism configured to collect contextual information associated with a consumer;

a determination mechanism configured to determine a current activity and/or a future activity in which the consumer is engaged based on the contextual information;

a prediction mechanism configured to predict one or more upcoming advertisement opportunities associated with the consumer based on the determined activities;

a presentation mechanism configured to present the predicted opportunities to one or more advertisers, thereby allowing the advertisers to determine a bid amount for presenting an advertisement at the predicted opportunities;

a selection mechanism configured to select at least one advertisement to present based on one or more of the following;

the bid amount, the collected contextual information, an occurrence probability of the predicted advertisement opportunities, content of the advertisement, metadata associated with the advertisement; and

a presentation mechanism configured to present the advertisement to the consumer.

18. The computer system of claim 17, further comprising a second determination mechanism configured to determine the consumer'"'"'s current and/or future receptivity based on the collected contextual information.

19. The computer system of claim 17, wherein the collected contextual information includes one or more of the following:

time of day;

day of week;

weather condition;

the consumer'"'"'s location;

speed of the consumer'"'"'s motion;

content of the consumer'"'"'s calendar, messages, and emails;

history of the consumer'"'"'s activities;

a statistical model constructed from the history of the consumer'"'"'s activities;

demographic statistics associated with the consumer; and

the consumer'"'"'s previous response to advertisement.

20. The computer system of claim 17, wherein the prediction mechanism is further configured to predict the one or more upcoming advertisement opportunities by calculating an opportunity score which is a time-varying function of the contextual information.

21. The computer system of claim 17, further comprising a second presentation mechanism configured to present the collected contextual information to the advertisers.

22. The computer system of claim 17, wherein while presenting the advertisement, the presentation mechanism is configured to present the advertisement to the consumer in-situ or proactively.

23. The computer system of claim 17, further comprising a similarity metric calculation mechanism configured to calculate a similarity metric between the consumer'"'"'s current situation and a known situation.

24. The computer system of claim 23, wherein the similarity metric calculation mechanism is further configured to calculate the similarity metric by performing at least one of:

comparing contextual information associated with the consumer'"'"'s current situation with contextual information associated with the consumer'"'"'s one or more past situations; and

fitting contextual information associated with the consumer'"'"'s current situation with a statistics model based on historical data associated with the consumer.