SYSTEMS AND METHODS FOR SEARCH RETARGETING USING DIRECTED DISTRIBUTED QUERY WORD REPRESENTATIONS

• US 20150379571A1
• Filed: 06/30/2014
• Published: 12/31/2015
• Est. Priority Date: 06/30/2014
• Status: Abandoned Application

• Current Assignee: Excalibur IP, LLC (Acacia Research Corporation)
• Original Assignee: Yahoo! Inc. (Apollo Global Management, Inc.)
• Inventors: Grbovic, Mihajlo, Djuric, Nemanja, Radosavljevic, Vladan, Bhamidipati, Narayan
• Application Number:
  US14/320,048
• Publication Number:
  US 20150379571A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06Q 30/0256 User search

Abstract

A system stored in a non-transitory medium executable by processor circuitry is provided for generating retargeting keywords based on distributed query word representations. The system includes one or more system databases storing historical web search data. Search retargeting circuitry receives requests to generate sets of retargeting keywords related to one or more categories of an advertisement campaign and pre-processing circuitry retrieves a set of historical web search data related to the one or more categories of the advertisement campaign. Modeling circuitry further applies one or more computational linguistic models to the retrieved set of historical web search data and generates distributed query word representations from the retrieved set of historical web search data. Keyword generator circuitry generates a list of retargeting keywords related to the one or more categories of the advertisement campaign using the generated distributed query word representations.

Claims

1. A system stored in a non-transitory medium executable by processor circuitry for generating retargeting keywords based on distributed query word representations, comprising:

one or more system databases storing historical web search data;

search retargeting circuitry that receives requests to generate sets of retargeting keywords related to one or more categories of an advertisement campaign;

pre-processing circuitry that retrieves a set of historical web search data related to the one or more categories of the advertisement campaign;

modeling circuitry that applies one or more computational linguistic models to the retrieved set of historical web search data and generates distributed query word representations from the retrieved set of historical web search data; and

keyword generator circuitry that generates a list of retargeting keywords related to the one or more categories of the advertisement campaign using the generated distributed query word representations.

2. The system of claim 1, wherein the historical web search data comprise historical search query terms submitted by users and ad click data related to user interactions with ad content.

3. The system of claim 1, further comprising a retargeting campaign generator that generates a set of search retargeting rules for the advertisement campaign based on the generated list of retargeting keywords.

4. The system of claim 3, further comprising monetization circuitry that receives a request to generate an advertisement specifying an ad category and applies one or more of the search retargeting rules to select an advertisement to display to a user.

5. The system of claim 1, wherein the distributed query word representations represent a likelihood that a user will click on an advertisement related to a particular category after the user enters a search query containing a keyword.

6. The system of claim 1, wherein the keyword generator circuitry further generates one or more vectors of keyword clusters of related keywords associated with the one or more categories of the advertisement campaign.

7. The system of claim 6, wherein the list of retargeting keywords is generated by selecting a predetermined number of the most closely related keywords associated with the one or more categories of the advertisement campaign.

8. The system of claim 1, wherein the one or more computational linguistic models comprises a model applying natural language processing to historical web search data.

9. The system of claim 8, the model applying natural language processing to historical web search data is based on a directed skip-gram model.

10. The system of claim 9, wherein the model based on the directed skip-gram model considers only user actions in the historical web search data that were taken within a predetermined timeframe of an ad click contained within the historical web search data for that user.

11. The system of claim 9, wherein the model based on the directed skip-gram model weights user actions in the historical web search data based on a timeframe proximity to an ad click contained within the historical web search data for that user.

12. The system of claim 1, wherein pre-processing circuitry further sessionizes the set of historical web search data by segmenting the data into a series of user sessions for each user.

13. The system of claim 12, wherein each user session in the series of user sessions comprises a series of ad clicks and search queries entered by the respective user within a predefined period of time.

14. The system of claim 12, wherein each user session in the series of user sessions begins with a user search query and ends after a predefined period of time.

15. The system of claim 2, wherein the modeling circuitry further trains the one or more computational linguistic models by processing the historical web search data to merge related forms of search query terms.

16. A computer-implemented method for generating retargeting keywords comprising:

processing, by search retargeting circuitry communicatively coupled to a network communications circuitry, a request to generate sets of retargeting keywords related to an advertisement campaign

processing, by pre-processing circuitry, the request to retrieve a set of historical web search data related to the advertisement campaign;

generating, by modeling circuitry, distributed query word representations from the retrieved set of historical web search data by applying one or more natural language processing models to the set of historical web search data; and

generating, by keyword generator circuitry, a list of retargeting keywords related to the advertisement campaign based on the distributed query word representations.

17. The computer-implemented method of claim 16, further comprising generating, by a retargeting campaign circuitry, a set of search retargeting rules for the advertisement campaign based on the generated list of retargeting keywords.

18. The computer-implemented method of claim 16, wherein the distributed query word representations associations between search query terms in the historical web search data and ad clicks of a user.

19. The computer-implemented method of claim 16, wherein the one or more natural language processing models applies to the historical web search data is based on a directed skip-gram model that only considers user actions in the historical web search data that were taken within a predetermined timeframe of an ad click.

20. A system for generating search retargeting keywords, comprising:

a means for receiving a request to generate retargeting keywords for an advertisement campaign;

a means for processing the request to identify historical web search data related to the advertisement campaign;

a means for generating distributed query word representations from the identified historical web search data by applying one or more natural language processing models to the identified historical web search data that considers user actions within a predetermined timeframe of an ad click; and

a means for generating a list of retargeting keywords related to the advertisement campaign based on the distributed query word representations.