DYNAMICALLY DETERMINING A SEARCH RADIUS TO SELECT ONLINE CONTENT
The disclosure relates to selecting content items via a computer network. A request for content, information related to a search query, and location data is received. A plurality of content items each associated with a business location are identified based on the received information. A feature representation for one or more features is generated based on received information, location data and business locations. A data structure storing optimum radii correlated with a presence of the features and a corresponding performance metric is accessed to determine a radius threshold. A radius threshold is determined based on the optimum radii and one or more feature representations. An eligible business location having a distance from the device that is within the determined radius threshold is identified. A content item associated with the eligible business location is selected as a candidate for display on the device.
1 . A method of selecting content via a computer network, comprising:
receiving, by a data processing system having one or more processors, a request for content, the request including information relating to a search query input to a device;
receiving location data associated with the device;
identifying, based on the received information, a plurality of content items each associated with a business location;
evaluating the received information, the location data and each business location to generate a feature representation for each of a plurality of features related to at least one of the received information, location data or each business location;
accessing a data structure storing, in a memory element, optimum radii correlated with a presence of the plurality of features and a corresponding performance metric based on indications of interest;
determining a radius threshold based on the optimum radii and one or more feature representations;
identifying an eligible business location having a distance from the device that is within the determined radius threshold; and
selecting, as a candidate for display on the device, one of the plurality of content items associated with the eligible business location.
2 . The method of claim 1 , wherein the plurality of features comprises at least one of a business location popularity, search query vertical, query data, device location, source of device location, or device activity.
3 . The method of claim 1 , wherein the corresponding performance metric satisfies a performance threshold, the corresponding performance metric comprising at least one of a click through rate or a conversion rate.
4 . The method of claim 1 , further comprising:
identifying a popularity feature representation for each business location associated with the plurality of content items based on at least one of a number of searches performed via a search engine, a rating, or a number of reviews.
5 . The method of claim 1 , further comprising:
determining, for a first business location, a first feature representation for a popularity feature;
determining, for a second business location, a second feature representation for the popularity feature, the second feature representation greater than the first feature representation; and
selecting a first radius threshold for the first business location based on the first feature representation, and a second radius threshold for the second business location based on the second feature representation, the second radius threshold greater than the first radius threshold.
6 . The method of claim 1 , further comprising:
determining, based on sensor data of the device, a feature representation for a device activity corresponding to a first device activity;
accessing the data structure storing a first radius threshold correlated with the first device activity and a second radius threshold correlated with a second device activity; and
dynamically selecting, based on the feature representation, the first radius threshold, the first radius threshold less than the second radius threshold.
7 . The method of claim 1 , further comprising:
using a decision tree machine learning model to predict a likelihood of interest in the business location based on the plurality of features.
8 . The method of claim 1 , further comprising:
providing historical search query logs and the plurality of features to a machine learning model to generate the data structure storing the optimum radii.
9 . The method of claim 8 , further comprising:
providing an indication of a request for directions to a business location associated with the historical search query logs.
10 . The method of claim 1 , further comprising:
dynamically selecting the radius threshold based on a combination of each feature representation for each of the plurality of features.
11 . The method of claim 1 , further comprising:
selecting one or more radii from the optimum radii; and
processing the selected one or more radii to determine the radius threshold.
12 . A system to select content via a computer network, comprising:
an interface, of a data processing system having one or more processors, configured to receive a request for content, the request including information relating to a search query input to a device;
a content selector, of the data processing system, configured to identify, based on the received information, a plurality of content items each associated with a business location;
a feature generator, of the data processing system, configured to:
evaluate the received information, the location data and each business location to generate a feature representation for each of a plurality of features related to at least one of the received information, location data or each business location;
access a data structure storing, in a memory element, optimum radii correlated with a presence of the plurality of features and a corresponding performance metric based on indications of interest;
determine a radius threshold based on the optimum radii and one or more feature representations;
a locator, of the data processing system, configured to identify an eligible business location having a distance from the device that is within the determined radius threshold; and
the content selector further configured to select, as a candidate for display on the device, one of the plurality of content items associated with the eligible business location.
13 . The system of claim 12 , wherein the plurality of features comprises at least one of a business location popularity, search query vertical, query data, device location, source of device location, or device activity.
14 . The system of claim 12 , wherein the data processing system is further configured to:
identify a popularity feature value for each business location associated with the plurality of content items based on at least one of a number of searches performed via a search engine, a rating, or a number of reviews.
15 . The system of claim 12 , wherein the corresponding performance metric satisfies a performance threshold, the corresponding performance metric comprising at least one of a click through rate or a conversion rate.
16 . The system of claim 12 , wherein the data processing system is further configured to:
determine, for a first business location, a first feature representation of a popularity feature;
determine, for a second business location, a second feature representation for the popularity feature, the second feature representation greater than the first feature representation; and
select a first radius threshold for the first business location based on the first feature representation, and a second radius threshold for the second business location based on the second feature representation, the second radius threshold greater than the first radius threshold.
17 . The system of claim 12 , wherein the data processing system is further configured to:
access the data structure storing a first radius threshold correlated with a first device activity and a second radius threshold correlated with a second device activity;
determine, based on sensor data of the device, a feature representation for a device activity corresponds to the first device activity; and
dynamically select, based on the feature representation, a first radius threshold, the first radius threshold less than the second radius threshold.
18 . The system of claim 12 , wherein the data processing system is further configured to:
use a decision tree machine learning model to predict a likelihood of interest in the business location based on the plurality of features.
19 . The system of claim 12 , wherein the data processing system is further configured to:
provide historical search query logs and the plurality of features to a machine learning model to generate the data structure.
20 . A computer-readable storage device comprising processor executable instructions to select content via a computer network, the instructions further comprising instructions to:
receive a request for content, the request including information relating to a search query input to a device;
receiving location data associated with the device;
identify, based on the received information, a plurality of content items each associated with a business location;
evaluate the received information, the location data and each business location to generate a feature representation for each of a plurality of features related to at least one of the received information, location data or each business location;
access a data structure storing, in a memory element, optimum radii correlated with a presence of the plurality of features and a corresponding performance metric based on indications of interest;
determine a radius threshold based on the optimum radii and one or more feature representations;
identify an eligible business location having a distance from the device that is within the determined radius threshold; and
select, as a candidate for display on the device, one of the plurality of content items associated with the eligible business location.