US 2019/0197077 A1Published application

Machine learning based identification of broken network connections

AssigneeGoogle Inc.

InventorsXin Li, Fang Yang

Life of this patent

Estimating the term…

Loading patent…

Abstract

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for identifying broken network connections. In one aspect, a system includes front-end server(s) that receive data specifying, for multiple different user interactions with one or more application links that link to a given application, presentation durations specifying how long application content linked to by the application link was presented following the multiple different user interactions with the application link(s). Back-end server(s) that communicate with the front end server(s) can classify each application link as broken or working based on application of a machine learning model to the presentation durations for the application link. The machine learning model can be generated using labeled training data. The back-end server(s) can generate and output an alert identifying an application link as a broken link based on the application link being classified as broken by the machine learning model.

Claims20

Dependent claims

A system comprising:

one or more front-end servers that receive data specifying, for multiple different user interactions with one or more application links that link to a given application, presentation durations specifying how long application content linked to by the application link was presented following the multiple different user interactions with the one or more application links;
and
one or more back-end servers that communicate with the one or more front end servers and perform operations including:
classifying each application link as broken or working based on application of a machine learning model to the presentation durations for the application link, wherein the machine learning model is generated using labeled training data that includes, for each training application link in a set of training application links:
a set of presentation durations for the training application link;
and
a label that specifies whether the training application link is broken or working based on whether a user interaction with the training application link resulted in successful presentation of content pointed to by the training application link;
and
generating and outputting an alert identifying a given application link as a broken link based on the given application link being classified as broken by the machine learning model.

6 more elements

A method performed by data processing apparatus, the method comprising:

receiving data specifying, for multiple different user interactions with one or more application links that link to a given application, presentation durations specifying how long application content linked to by the application link was presented following the multiple different user interactions with the one or more application links;
classifying each application link as broken or working based on application of a machine learning model to the presentation durations for the application link, wherein the machine learning model is generated using labeled training data that includes, for each training application link in a set of training application links:
a set of presentation durations for the training application link;
and
a label that specifies whether the training application link is broken or working based on whether a user interaction with the training application link resulted in successful presentation of content pointed to by the training application link;
and
generating and outputting an alert identifying a given application link as a broken link based on the given application link being classified as broken by the machine learning model.

4 more elements

A computer storage medium encoded with a computer program, the program comprising instructions that when executed by data processing apparatus cause the data processing apparatus to perform operations comprising:

receiving data specifying, for multiple different user interactions with one or more application links that link to a given application, presentation durations specifying how long application content linked to by the application link was presented following the multiple different user interactions with the one or more application links;
classifying each application link as broken or working based on application of a machine learning model to the presentation durations for the application link, wherein the machine learning model is generated using labeled training data that includes, for each training application link in a set of training application links:
a set of presentation durations for the training application link;
and
a label that specifies whether the training application link is broken or working based on whether a user interaction with the training application link resulted in successful presentation of content pointed to by the training application link;
and
generating and outputting an alert identifying a given application link as a broken link based on the given application link being classified as broken by the machine learning model.

4 more elements

Dependencies are inferred from the claim text.

Facts

Application: 15/318,229Filed 17 Oct 2016
Published: 27 Jun 2019
Term ends: Not estimatedThe source records don’t support an estimate.

Classification21 codes

G06F 16/9566
Using information identifiers, e.g. uniform resource locators [URL]: uRL specific, e.g. using aliases, detecting broken or misspelled links
G06F 16/9558
Using information identifiers, e.g. uniform resource locators [URL]: details of hyperlinks; Management of linked annotations
G06N 20/00
Machine learning
H04L 41/16
Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks: using machine learning…