Characterizing international orientation

Patent metadata

Field	Value
Publication number	US-2020364275-A1
Application number	US-201916410015-A
Country	US
Kind code	A1
Filing date	May 13, 2019
Priority date	May 13, 2019
Publication date	Nov 19, 2020
Grant date	—

Abstract

The disclosed embodiments provide a system for processing data. During operation, the system obtains labels representing an international orientation or a non-international orientation of a first set of members of an online system, wherein the international orientation includes an interest in or an exposure to foreign entities. Next, the system inputs the labels with features for the first set of members as training data for a machine learning model. The system then applies one or more rules derived from the machine learning model to additional features for a second set of members of the online system to classify some or all members in the second set of members as having the international orientation or the non-international orientation. Finally, the system outputs one or more attributes associated with the classified members for use in improving use of the online system by the members.

First claim

What is claimed is:

1 . A method, comprising:
obtaining labels representing an international orientation or a non-international orientation of a first set of members of an online system, wherein the international orientation comprises an interest in or an exposure to one or more foreign entities; inputting, by one or more computer systems, the labels with features for the first set of members as training data for a machine learning model; applying, by the one or more computer systems, one or more rules derived from the machine learning model to additional features for a second set of members of the online system to classify some or all members in the second set of members as having the international orientation or the non-international orientation; and outputting one or more attributes associated with the classified members for use in improving use of the online system by the second set of members.

2 . The method of claim 1 , further comprising:
identifying a third set of members of the online system as having the international orientation based on one or more profile attributes of the third set of members.

3 . The method of claim 2 , wherein the one or more profile attributes comprise a foreign user interface locale for the online system.

4 . The method of claim 3 , wherein the one or more profile attributes further comprise at least one of:
foreign work experience; and registration with the online system from a foreign location.

5 . The method of claim 1 , wherein obtaining the labels representing the international orientation or the non-international orientation of the first set of members of the online system comprises:
generating clusters of the first set of members; and obtaining a label of the international orientation or the non-international orientation for each of the clusters.

6 . The method of claim 1 , wherein applying the one or more rules derived from the machine learning model to the additional features for the second set of members comprises:
creating the one or more rules from a subset of parameters for the machine learning model.

7 . The method of claim 1 , wherein the features comprise a proportion of foreign connections for a member.

8 . The method of claim 7 , wherein the one or more rules comprise a minimum threshold for the proportion of foreign connections for the member to have the international orientation.

9 . The method of claim 1 , wherein the one or more rules comprise foreign education experience for a member to have the international orientation.

10 . The method of claim 1 , further comprising:
generating a recommendation related to use of the online system based on the one or more attributes.

11 . The method of claim 10 , wherein the recommendation comprises at least one of:
a connection for increasing engagement with the online system; a channel for acquiring additional members with the international orientation or the non-international orientation; and a product strategy for improving use of the online system by the second set of members.

12 . The method of claim 1 , wherein the one or more attributes associated with the classified second set of members comprises at least one of:
a metric related to the classified second set of members; a distribution of the international orientation and the non-international orientation in the classified second set of members; and a profile attribute shared by members with the international orientation or the non-international orientation.

13 . A system, comprising:
one or more processors; and memory storing instructions that, when executed by the one or more processors, cause the system to:
obtain labels representing an international orientation or a non-international orientation of a first set of members of an online system, wherein the international orientation comprises an interest in or an exposure to one or more foreign entities;
input the labels with features for the first set of members as training data for a machine learning model;
apply one or more rules derived from the machine learning model to additional features for a second set of members of the online system to classify some or all members in the second set of members as having the international orientation or the non-international orientation; and
output one or more attributes associated with the classified members for use in improving use of the online system by the classified members.

14 . The system of claim 13 , wherein the memory further stores instructions that, when executed by the one or more processors, cause the system to:
identify a third set of members of the online system as having the international orientation based on one or more profile attributes of the third set of members.

15 . The system of claim 14 , wherein the one or more profile attributes comprise at least one of:
a foreign user interface locale for the online system; foreign work experience; and registration with the online system from a foreign location.

16 . The system of claim 13 , wherein obtaining the labels representing the international orientation or the non-international orientation of the first set of members of the online system comprises:
generating clusters of the first set of members; and obtaining a label of the international orientation or the non-international orientation for each of the clusters.

17 . The system of claim 13 , wherein applying the one or more rules derived from the machine learning model to the additional features for the second set of members comprises:
creating the one or more rules from one or more conditions in a decision tree.

18 . The system of claim 13 , wherein the one or more rules comprise at least one of:
a minimum threshold for a proportion of foreign connections for a member to have the international orientation; and foreign education experience for the member to have the international orientation.

19 . The system of claim 13 , wherein the one or more foreign entities comprise at least one of:
a company; a school; a location; and a member.

20 . A non-transitory computer-readable storage medium storing instructions that when executed by a computer cause the computer to perform a method, the method comprising:
obtaining labels representing an international orientation or a non-international orientation of a first set of members of an online system, wherein the international orientation comprises an interest in or an exposure to one or more foreign entities; inputting the labels with features for the first set of members as training data for a machine learning model; applying one or more rules derived from the machine learning model to additional features for a second set of members of the online system to classify some or all members in the second set of members as having the international orientation or the non-international orientation; and outputting one or more attributes associated with the classified members for use in improving use of the online system by the classified members.

Assignees

• Microsoft Technology Licensing Llc

Inventors

• Liu Yang
• Wang Li
• Fu Xin
• Zhang Wenjing
• Manwani Hitesh

Classifications

• G06N5/01

  Dynamic search techniques; Heuristics; Dynamic trees; Branch-and-bound · CPC title

• G06Q10/06

  Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling · CPC title

• G06N20/00

  Machine learning · CPC title

• G06Q10/42

  Determination of affinities or common interests between users · CPC title

• G06F16/958 Primary

  Organisation or management of web site content, e.g. publishing, maintaining pages or automatic linking · CPC title