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Home / Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence / EAAI-20

Relation Structure-Aware Heterogeneous Information Network Embedding

February 1, 2023

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Authors

Yuanfu Lu

Beijing University of Posts and Telecommunications


Chuan Shi

Beijing University of Posts and Telecommunications


Linmei Hu

Beijing University of Posts and Telecommunications


Zhiyuan Liu

Tsinghua University


DOI:

10.1609/aaai.v33i01.33014456


Abstract:

Heterogeneous information network (HIN) embedding aims to embed multiple types of nodes into a low-dimensional space. Although most existing HIN embedding methods consider heterogeneous relations in HINs, they usually employ one single model for all relations without distinction, which inevitably restricts the capability of network embedding. In this paper, we take the structural characteristics of heterogeneous relations into consideration and propose a novel Relation structure-aware Heterogeneous Information Network Embedding model (RHINE). By exploring the real-world networks with thorough mathematical analysis, we present two structure-related measures which can consistently distinguish heterogeneous relations into two categories: Affiliation Relations (ARs) and Interaction Relations (IRs). To respect the distinctive characteristics of relations, in our RHINE, we propose different models specifically tailored to handle ARs and IRs, which can better capture the structures and semantics of the networks. At last, we combine and optimize these models in a unified and elegant manner. Extensive experiments on three real-world datasets demonstrate that our model significantly outperforms the state-of-the-art methods in various tasks, including node clustering, link prediction, and node classification.

Topics: AAAI

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HOW TO CITE:

Yuanfu Lu||Chuan Shi||Linmei Hu||Zhiyuan Liu Relation Structure-Aware Heterogeneous Information Network Embedding Proceedings of the AAAI Conference on Artificial Intelligence (2019) 4456-4463.

Yuanfu Lu||Chuan Shi||Linmei Hu||Zhiyuan Liu Relation Structure-Aware Heterogeneous Information Network Embedding AAAI 2019, 4456-4463.

Yuanfu Lu||Chuan Shi||Linmei Hu||Zhiyuan Liu (2019). Relation Structure-Aware Heterogeneous Information Network Embedding. Proceedings of the AAAI Conference on Artificial Intelligence, 4456-4463.

Yuanfu Lu||Chuan Shi||Linmei Hu||Zhiyuan Liu. Relation Structure-Aware Heterogeneous Information Network Embedding. Proceedings of the AAAI Conference on Artificial Intelligence 2019 p.4456-4463.

Yuanfu Lu||Chuan Shi||Linmei Hu||Zhiyuan Liu. 2019. Relation Structure-Aware Heterogeneous Information Network Embedding. "Proceedings of the AAAI Conference on Artificial Intelligence". 4456-4463.

Yuanfu Lu||Chuan Shi||Linmei Hu||Zhiyuan Liu. (2019) "Relation Structure-Aware Heterogeneous Information Network Embedding", Proceedings of the AAAI Conference on Artificial Intelligence, p.4456-4463

Yuanfu Lu||Chuan Shi||Linmei Hu||Zhiyuan Liu, "Relation Structure-Aware Heterogeneous Information Network Embedding", AAAI, p.4456-4463, 2019.

Yuanfu Lu||Chuan Shi||Linmei Hu||Zhiyuan Liu. "Relation Structure-Aware Heterogeneous Information Network Embedding". Proceedings of the AAAI Conference on Artificial Intelligence, 2019, p.4456-4463.

Yuanfu Lu||Chuan Shi||Linmei Hu||Zhiyuan Liu. "Relation Structure-Aware Heterogeneous Information Network Embedding". Proceedings of the AAAI Conference on Artificial Intelligence, (2019): 4456-4463.

Yuanfu Lu||Chuan Shi||Linmei Hu||Zhiyuan Liu. Relation Structure-Aware Heterogeneous Information Network Embedding. AAAI[Internet]. 2019[cited 2023]; 4456-4463.


ISSN: 2374-3468


Published by AAAI Press, Palo Alto, California USA
Copyright 2022, Association for the Advancement of
Artificial Intelligence 1900 Embarcadero Road, Suite
101, Palo Alto, California 94303 All Rights Reserved

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