ECONOMIC OPTIMIZATION FOR PRODUCT SEARCH RELEVANCY

• US 20160117609A1
• Filed: 01/04/2016
• Published: 04/28/2016
• Est. Priority Date: 06/26/2007
• Status: Active Grant

• Current Assignee: PayPal, Inc. (PayPal Holdings, Inc.)
• Original Assignee: PayPal, Inc. (PayPal Holdings, Inc.)
• Inventors: Billingsley, Eric Noel, Gupta, Raghav, Shoup, Randall Scott, Sundaresan, Neelakantan
• Granted Patent: US 10,430,724 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/9577 Optimising the visualization of content, e.g. distillation of HTML documents
• CPC Class Codes: G06F 16/958 Organisation or management of web site content, e.g. publishing, maintaining pages or automatic linking
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: G06N 5/022 Knowledge engineering; Knowledge acquisition
• CPC Class Codes: G06Q 10/06375 Prediction of business process outcome or impact based on a proposed change
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 40/06 Asset management; Financial planning or analysis

Abstract

In one embodiment, a method is illustrated as including defining a set of perspective objects capable of being placed onto a modified web page, monitoring parameters of a web page, the parameters including a number of times a current object is executed on the web page, using an Artificial Intelligence (AI) algorithm to determine a perspective object with a preferred Return On Investment (ROI), and selecting the perspective object to be placed onto the modified web page.

Claims

1. A method comprising:

defining a set of perspective objects capable of being placed onto a modified web page;

monitoring parameters of a web page, the parameters including a number of times a current object is executed on the web page;

using an Artificial Intelligence (AI) algorithm to determine a perspective object with a preferred Return On Investment (ROI); and

selecting the perspective object to be placed onto the modified web page.

2. The method of claim 1, further comprising:

listening to website traffic, the website traffic including content request data relating to a specific transaction; and

capturing the content request data, and storing the content request data.

3. The method of claim 1, further comprising

a traffic monitor to listen to website traffic, the website traffic including user response data relating to a specific transaction;

and

a data capture to capture the user response data, and storing the user response data.

4. The method of claim 1, further comprising:

updating a decision tree to reflect recent search queries, the decision tree containing members of a traffic optimizer module set as nodes; and

traversing the decision tree and selecting a member of the traffic optimizer module set, the selection based upon the member of the traffic optimizer module set with the preferred ROI value.

5. The method of claim 2, further comprising creating a histogram relating to keyword usage, the histogram containing a portion of the content request data, and that identifies the member of the traffic optimizer module set.

6. The method of claim 1, further comprising calculating the preferred ROI based upon a difference between a cost associated with generating the web page, and a revenue amount generated by the web page.

7. The method of claim 1, further comprising calculating the preferred ROI relative to other possible ROI values resulting from the presentation of the web page.

8. The method of claim 1, further comprising:

retrieving a batch of histograms and item types;

categorizing each histogram of the batch of histograms based upon the item type, the item type including items to be sold;

filtering the batch of histograms using a configuration rules set, the filtering to remove histograms from the batch of histograms that violate a rule in the configuration rules set; and

sorting the batch of histograms.

9. The method of claim 8, further comprising:

dividing the batch of histograms by classification, the classification relating each member of the batch of histograms to one or more members of a traffic optimizer module set; and

selecting one or more histogram from the batch of histograms, the selecting based upon the histograms relationship to a member of the traffic optimizer module set.

10. The method of claim 9, wherein the one or more members of the traffic optimizer module set includes at least one of a page-type, merchandising, ad, or navigation module.

11. The method of claim 8, further comprising:

retrieving a histogram from the batch of histograms;

retrieving object data associated with the histogram, the retrieving based upon a preferred ROI value as determined by one or more AI algorithms; and

transmitting a object associated with the object data as part of a web page instruction set.

12. A computer system comprising:

a set definition engine to define a set of perspective objects capable of being placed onto a modified web page;

a monitor to monitor parameters of a web page, the parameters including a number of times a current object is executed on the web page;

an Artificial Intelligence (AI) engine to use an AI algorithm to determine a perspective object with a preferred Return On Investment (ROI); and

a selection engine to select the perspective object to be placed onto the modified web page.

13. The computer system of claim 12, further comprising:

a traffic monitor to listen to website traffic, the website traffic including content request data relating to a specific transaction; and

a data capture to capture the content request data, and storing the content request data.

14. The computer system of claim 12, further comprising

a traffic monitor to listen to website traffic, the website traffic including user response data relating to a specific transaction;

and

a data capture to capture the user response data, and storing the user response data.

15. The computer system of claim 12, further comprising:

an update module to update a decision tree to reflect recent search queries, the decision tree containing members of a traffic optimizer module set as nodes; and

a traversal module to traverse the decision tree and selecting a member of the traffic optimizer module set, the selection based upon the member of the traffic optimizer module set with the preferred ROI value.

16. The computer system of claim 12, further comprising a histogram engine to create a histogram relating to keyword usage, the histogram containing a portion of the content request data, and that identifies the member of the traffic optimizer module set.

17. The computer system of claim 12, further comprising a calculator to calculate the preferred ROI based upon a difference between a cost associated with generating the web page, and a revenue amount generated by the web page.

18. The computer system of claim 12, further comprising a calculator to calculate the preferred ROI relative to other possible ROI values resulting from the presentation of the web page.

19. The computer system of claim 12, further comprising:

a first retrieval engine to retrieve a batch of histograms and item types;

a category engine to categorize each histogram of the batch of histograms based upon the item type, the item type including items to be sold;

a filter to filter the batch of histograms using a configuration rules set, the filtering to remove histograms from the batch of histograms that violate a rule in the configuration rules set; and

a sorting engine to sort the batch of histograms.

20. The computer system of claim 19, further comprising:

a classification engine to divide the batch of histograms by classification, the classification relating each member of the batch of histograms to one or more members of a traffic optimizer module set; and

a histogram selector to select one or more histograms from the batch of histograms, the selecting based upon the histograms relationship to a member of the traffic optimizer module set.

21. The computer system of claim 20, wherein the one or more members of the traffic optimizer module set includes at least one of a page-type, merchandising, ad, or navigation module.

22. The computer system of claim 19, further comprising:

a second retrieval engine to retrieve a histogram from the batch of histograms;

a third retrieval engine to retrieve object data associated with the histogram, the retrieving based upon a preferred ROI value as determined by one or more AI algorithms; and

a transmitter to transmit a object associated with the object data as part of a web page instruction set.

23. An apparatus comprising:

means for defining a set of perspective objects capable of being placed onto a modified web page;

means for monitoring parameters of a web page, the parameters including a number of times a current object is executed on the web page;

means for using an Artificial Intelligence (AI) algorithm to determine a perspective object with a preferred Return On Investment (ROI); and

means for selecting the perspective object to be placed onto the modified web page.

24. A machine-readable medium comprising instructions, which when implemented by one or more machines that cause the one or more machines to perform the following operations:

defining a set of perspective objects capable of being placed onto a modified web page;

monitoring parameters of a web page, the parameters including a number of times a current object is executed on the web page;

using an Artificial Intelligence (AI) algorithm to determine a perspective object with a preferred Return On Investment (ROI); and

selecting the perspective object to be placed onto the modified web page.