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Method and system of utilizing unsupervised learning to improve text to content suggestions

An unsupervised, content-based technique, applied in the field of using unsupervised learning to improve text-to-content recommendations and systems, can solve the problem of not being able to present new content to users

Pending Publication Date: 2021-02-19
MICROSOFT TECH LICENSING LLC
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

This may mean that even if new content is added to the service, it may not be presented to the user for a long period of time

Method used

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  • Method and system of utilizing unsupervised learning to improve text to content suggestions
  • Method and system of utilizing unsupervised learning to improve text to content suggestions
  • Method and system of utilizing unsupervised learning to improve text to content suggestions

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Embodiment Construction

[0017] In the following detailed description, numerous specific details are set forth by way of example in order to provide a thorough understanding of the relevant teachings. After reading this specification, it will be apparent to one of ordinary skill that the various aspects can be practiced without the use of these details. In other instances, well-known methods, procedures, components and / or circuits have been described at a relatively high level and have not been described in detail so as not to unnecessarily obscure aspects of the present teachings.

[0018] Many applications commonly employed by a typical computer user may include content other than text used to enter data in the application. New content is frequently added to these applications, and each content can include a large number of different content, such as images, icons, emoji, and so on. As a result, it is often difficult and time-consuming for a user to view large amounts of content to find content tha...

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Abstract

Method and system for training a text-to-content suggestion ML model include accessing a dataset containing unlabeled training data collected from an application, the unlabeled training data being collected under user privacy constraints, applying an ML model to the dataset to generate a pretrained embedding, and applying a supervised ML model to a labeled dataset to train the text-to-content suggestion ML model utilized by the application by utilizing the pretrained embedding generated by the supervised ML model.

Description

Background technique [0001] Intelligent text-to-content suggestion services are used in a wide variety of computer programs. For example, a text-to-content suggestion service may be used to suggest images, icons or emoji based on text received as input in an application. Typically, such applications may be subject to certain privacy and data regulations. Therefore, these applications may not be able to store and use entered user data. In fact, they can exploit mechanisms such as masking certain words and not maintaining the original sentence order of the input text to ensure privacy. This makes it difficult to do text-to-content suggestion correctly. [0002] In addition, new content is frequently provided to applications that provide text-to-content suggestions. Because the process of tagging new content is often time-consuming and laborious, some new content may be untagged. In general, the more labeled data your model contains, the better the quality of the recommendat...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/332G06F16/33G06N20/00
CPCG06F40/30G06F40/274G06F40/40G06N3/082G06N3/088G06F40/284G06F40/216G06N3/048G06N3/045G06N20/20
Inventor 李骥张星星韦福如周明A·斯里瓦斯塔瓦
Owner MICROSOFT TECH LICENSING LLC