Enhancement of machine learning techniques for an electronic message system
First Claim
1. A computer system comprising:
- a data store that stores a machine learning model and data that indicates which users of a plurality of users are associated with which projects of a set of projects;
one or more computing devices, operatively coupled to the data store, and programmed to;
identify a first user and a second user associated with a first electronic message;
based on the data from the data store, determine a first subset of projects, from the set of projects, that are associated with the first user;
based on the data from the data store, determine a second subset of projects, from the set of projects, that are associated with the second user;
compare the first subset of projects to the second subset of projects to determine a third subset of projects that are common to both the first subset of projects and the second subset of projects;
wherein the third subset of projects includes at least two projects that are in both the first subset of projects and the second subset of projects;
wherein the third subset of projects includes less than all of the set of projects;
collect one or more first features associated with each project of the third subset of projects;
for only those projects that belong to the third subset of projects, generate a project score that reflects likelihood that the first electronic message is related to the project, based at least in part on;
the machine learning model, andthe one or more first features associated with the project;
determine that a particular project has a higher project score than any other project in the third subset of projects; and
in response to determining that the particular project has a higher project score than any other project in the third subset of projects, associate the first electronic message with the particular project.
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Abstract
Techniques are described herein for classifying an electronic message with a particular project from among a plurality of projects. In some embodiments, first and second users associated with the electronic message are identified, and one or more first projects associated with the first user and one and more second projects associated with the second user are determined. Projects that are in common between the first projects and the second projects are determined. When only a single project is in common, the electronic message is associated with the single project. When more than a single project is in common, features associated with each of the projects found to be in common are analyzed by a machine learning model to determine the most likely project to associate with the electronic message from among the projects found to be in common.
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Citations
20 Claims
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1. A computer system comprising:
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a data store that stores a machine learning model and data that indicates which users of a plurality of users are associated with which projects of a set of projects; one or more computing devices, operatively coupled to the data store, and programmed to; identify a first user and a second user associated with a first electronic message; based on the data from the data store, determine a first subset of projects, from the set of projects, that are associated with the first user; based on the data from the data store, determine a second subset of projects, from the set of projects, that are associated with the second user; compare the first subset of projects to the second subset of projects to determine a third subset of projects that are common to both the first subset of projects and the second subset of projects; wherein the third subset of projects includes at least two projects that are in both the first subset of projects and the second subset of projects; wherein the third subset of projects includes less than all of the set of projects; collect one or more first features associated with each project of the third subset of projects; for only those projects that belong to the third subset of projects, generate a project score that reflects likelihood that the first electronic message is related to the project, based at least in part on; the machine learning model, and the one or more first features associated with the project; determine that a particular project has a higher project score than any other project in the third subset of projects; and in response to determining that the particular project has a higher project score than any other project in the third subset of projects, associate the first electronic message with the particular project. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
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11. A method comprising:
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obtaining data that indicates which users of a plurality of users are associated with which projects of a set of projects; identifying a first user and a second user associated with a first electronic message; based on the data from the data store, determining a first subset of projects, from the set of projects, that are associated with the first user; based on the data from the data store, determining a second subset of projects, from the set of projects, that are associated with the second user; comparing the first subset of projects to the second subset of projects to determine a third subset of projects that are common to both the first subset of projects and the second subset of projects; wherein the third subset of projects includes at least two projects that are in both the first subset of projects and the second subset of projects; wherein the third subset of projects includes less than all of the set of projects; collecting one or more first features associated with each project of the third subset of projects; for only those projects that belong to the third subset projects, generating a project score that reflects likelihood that the first electronic message is related to the project, based at least in part on; a machine learning model, and the one or more first features associated with the project; determining that a particular project has a higher project score than any other project in the third subset of projects; and in response to determining that the particular project has a higher project score than any other project in the third subset of projects, associating the first electronic message with the particular project; wherein the method is performed by one or more computing devices. - View Dependent Claims (12, 13, 14, 15, 16, 17, 18, 19, 20)
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Specification