The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Jul. 13, 2021

Filed:

Dec. 04, 2015
Applicant:

A9.com, Inc., Palo Alto, CA (US);

Inventors:

Bing Yin, Fremont, CA (US);

Francois Huet, Santa Cruz, CA (US);

Christopher Varano, Redwood City, CA (US);

Assignee:

A9.com, Inc., Palo Alto, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06Q 30/00 (2012.01); G06Q 30/06 (2012.01);
U.S. Cl.
CPC ...
G06Q 30/0625 (2013.01); G06Q 30/0641 (2013.01);
Abstract

The arrangement and selection of digital content to present to a user can be based at least in part upon probabilities of the user selecting to view more information and/or entering into a transaction with respect to instances of the content. For example, user behavior with respect to various items provided through a content provider can be determined in order to calculate a probability that a user was searching for a particular type of item for a given search. The user behavior can include historical action data, such as information that indicates items that were selected in response to a particular search and/or items that were purchased in response to a particular search. The historical action data can be analyzed to generate an index that indicates a likelihood that the search was intended for a particular type of product. Additionally, the historical data can be used to train language models that can be used to determine a probability of interest for a particular type of product for a given search. Once a query is received, items of interest can be determined using one of the index or language models, and those items can be presented to the user.


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