Publication Type

Conference Proceeding Article

Version

publishedVersion

Publication Date

9-2021

Abstract

Graph embedding, aiming to learn low-dimensional representations of nodes while preserving valuable structure information, has played a key role in graph analysis and inference. However, most existing methods deal with static homogeneous topologies, while graphs in real-world scenarios are gradually generated with different-typed temporal events, containing abundant semantics and dynamics. Limited work has been done for embedding dynamic heterogeneous graphs since it is very challenging to model the complete formation process of heterogeneous events. In this paper, we propose a novel Heterogeneous Hawkes Process based dynamic Graph Embedding (HPGE) to handle this problem. HPGE effectively integrates the Hawkes process into graph embedding to capture the excitation of various historical events on the current type-wise events. Specifically, HPGE first designs a heterogeneous conditional intensity to model the base rate and temporal influence caused by heterogeneous historical events. Then the heterogeneous evolved attention mechanism is designed to determine the fine-grained excitation to different-typed current events. Besides, we deploy the temporal importance sampling strategy to sample representative events for efficient excitation propagation. Experimental results demonstrate that HPGE consistently outperforms the state-of-the-art alternatives.

Keywords

dynamic heterogeneous graph, graph embedding, heterogeneous Hawkes process, heterogeneous evolved attention mechanism

Discipline

Artificial Intelligence and Robotics | Databases and Information Systems

Research Areas

Data Science and Engineering; Intelligent Systems and Optimization

Publication

Proceedings of The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases 2021

Volume

Part I

First Page

388

Last Page

403

ISBN

978-3-030-86485-9

Identifier

10.1007/978-3-030-86486-6_24

City or Country

Virtual Event, Spain

Download

Share

COinS