TECHNIQUES FOR DETERMINING RELEVANT ADVERTISEMENTS IN RESPONSE TO QUERIES

• US 20080109285A1
• Filed: 10/26/2007
• Published: 05/08/2008
• Est. Priority Date: 10/26/2006
• Status: Abandoned Application

• Current Assignee: Mobile Content Networks Incorporated
• Original Assignee: Mobile Content Networks Incorporated
• Inventors: Connor, Michael, Reuther, Phyllis, Kurtz, David
• Application Number:
  US11/925,354
• Publication Number:
  US 20080109285A1
• Time in Patent Office: Days
• US Class Current: 705/7
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques
• CPC Class Codes: G06Q 10/063 Operations research, analysis or management
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0242 Determining effectiveness of advertisements

Abstract

Techniques for determining relevant advertisements in response to queries is disclosed. According to an exemplary embodiment of the present disclosure, the techniques may be realized as a computer implemented method for determining relevant advertisements in response to a query. The method may comprise: receiving a query from a user device; categorizing the query to identify one or more relevant advertisement sources; formatting the query according to one or more advertisement source specifics for the one or more advertisement sources; transmitting the formatted query to the one or more advertisement sources; merging results in response to the formatted query to the one or more advertisement sources; merging results based at least in part on one or more factors; and formatting the results for delivering to the user device.

Claims

1. A computer implemented method for determining relevant advertisements in response to a query, the method comprising:

receiving a query from a user device;

categorizing the query to identify one or more advertisement sources;

formatting the query according to one or more advertisement source specifics for the one or more advertisement sources;

transmitting the formatted query to the one or more advertisement sources;

merging results in response to the formatted query from the one or more advertisement sources based at least in part on one or more factors; and

formatting the results for delivering to the user device.

2. The method of claim 1, wherein the user device comprises one or more of an internet-enabled input device, an internet or voice-enabled mobile device, a voice-enabled input device, a computer, and a kiosk.

3. The method of claim 1, wherein the one or more factors comprise one or more global factors, local factors, editorial rating, response reliability, response latency, content relevance, content extensiveness or coverage, user preferences, usage statistics, query frequency, category frequency, distributor preferences, recommendation statistics, user-generated ratings, business relationships, user demographic characteristics, location, language, social networks, social groups, personalization characteristics, page size, graphic, text elements, source rating, reliability factor, business rules, business relationships, marketing goals, local ranking scores, source ordering values, source-specific general scores, statistics associated with results item textual or non-textual analysis, statistics associated with data or text mining analyses, statistics associated with data or textual clustering, statistics associated with non-textual pattern analysis, statistics associated with device specifics and/or statistics associated with formatting specifications.

4. The method of claim 1, wherein the query is classified into a category in one or more taxonomy or controlled vocabulary.

5. The method of claim 1, further comprising:

dynamically computing one or more local ranking statistics for each results item related to one or more terms associated with the query and related to metadata in the query context in response to the query, at each advertisement source.

6. The method of claim 1, further comprising:

computing at least one global and/or one local statistic related to one or more content items in the results sets;

determining one or more relevancy scores for the results items from the one or more advertisement sources in accordance with the at least one global and/or one local statistic;

computing a normalization factor;

normalizing the one or more relevancy scores in accordance with the normalization factor; and

combining the results into a single results set based on an ordering determined by the normalization factor.

7. The method of claim 1, further comprising:

storing results from each advertisement source in one or more caches;

accessing the one or more caches to retrieve existing results; and

formatting the retrieved existing results based on one or more query context parameters.

8. The method of claim 1, wherein categorizing the query occurs dynamically at the time the query is received.

9. The method of claim 1, further comprising:

identifying one or more duplicate result items.

10. The method of claim 9, further comprising:

removing the one or more duplicate result items according to one or more of user preference, device preference and distributor preference.

11. The method of claim 9, further comprising:

retaining the one or more duplicate results according to one or more of user preference, device preference and distributor preference.

12. A computer readable media comprising code to perform the acts of the method of claim 1.

13. A computer implemented system for determining relevant advertisements in response to a query, the system comprising:

a receiving module for receiving a query from a user device;

a categorizing module for categorizing the query to identify one or more advertisement sources;

a formatting module for formatting the query according to one or more advertisement source specifics for the one or more advertisement sources;

a transmitting module for transmitting the formatted query to the one or more advertisement sources;

a merging module for merging results in response to the formatted query from the one or more advertisement sources based at least in part on one or more factors; and

a results module for formatting the results for delivering to the user device.

14. The system of claim 13, wherein the user device comprises one or more of an internet-enabled input device, an internet or voice-enabled mobile device, a voice-enabled input device, a computer, and a kiosk.

15. The system of claim 13, wherein the one or more factors comprise one or more global factors, local factors, editorial rating, response reliability, response latency, content relevance, content extensiveness or coverage, user preferences, usage statistics, query frequency, category frequency, distributor preferences, recommendation statistics, user-generated ratings, business relationships, user demographic characteristics, location, language, social networks, social groups, personalization characteristics, page size, graphic, text elements, source rating, reliability factor, business rules, business relationships, marketing goals, local ranking scores, source ordering values, source-specific general scores, statistics associated with results item textual or non-textual analysis, statistics associated with data or text mining analyses, statistics associated with data or textual clustering, statistics associated with non-textual pattern analysis, statistics associated with device specifics and/or statistics associated with formatting specifications.

16. The system of claim 13, wherein the query is classified into a category in one or more taxonomy or controlled vocabulary.

17. The system of claim 13, further comprising:

a module for dynamically computing one or more local ranking statistics for each results item related to one or more terms associated with the query and related to metadata in the query context in response to the query, at each advertisement source.

18. The system of claim 13, further comprising:

a module for computing at least one global and/or one local statistic related to one or more content items in the results sets, wherein one or more relevancy scores are determined for the results items from the one or more advertisement sources in accordance with the at least one global and/or one local statistic; and

a module for computing a normalization factor, wherein the one or more relevancy scores are normalized in accordance with the normalization factor; and

the results are combined into a single results set based on an ordering determined by the normalization factor.

19. The system of claim 13, further comprising:

one or more caches for storing results from each advertisement source, wherein the one or more caches are accessed to retrieve existing results; and

wherein the retrieved existing results are formatted based on one or more query context parameters.

20. The system of claim 13, wherein categorizing the query occurs dynamically at the time the query is received.

21. The system of claim 13, wherein one or more duplicate results are identified.

22. The system of claim 21, wherein the one or more duplicate results are removed according to one or more of user, device and distributor preferences.

23. The system of claim 21, wherein the one or more duplicate results are retained according to one or more of user, device and distributor preferences.