Deep representation machine learned model for heterogeneous information networks

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United States of America Patent

PATENT NO 11941057
APP PUB NO 20230394084A1
SERIAL NO

17830067

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Abstract

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In an example embodiment, a deep learning model is used to learn embedding representations of a heterogeneous information network, where the embedding represents entity-specific properties and network environment properties. Position-aware embeddings specific to the heterogeneous information network may be used as input features of the deep learning model. Furthermore, meta-path embedding specific to the heterogeneous information network may also be used as input features of the deep learning model. Modified embedding propagation methods are further designed to explore better ways to capture network meta-path properties.

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Patent Owner(s)

  • MICROSOFT TECHNOLOGY LICENSING, LLC.

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Inventor(s)

Inventor Name Address # of filed Patents Total Citations
Evans, Kathryn L San Francisco, US 1 0
Jain, Aastha Sunnyvale, US 33 181
Liu, Zhanglong Fremont, US 2 1
Nigam, Aastha Sunnyvale, US 4 0
Saha, Ankan San Francisco, US 22 81
Xiao, Yiou Sunnyvale, US 4 4

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