Publication Type

Conference Proceeding Article

Version

acceptedVersion

Publication Date

11-2021

Abstract

In this demo, we present an online multi-modal community query engine (MQE1 ) on Alibaba’s billion-scale heterogeneous network. MQE has two distinct features in comparison with existing community query engines. Firstly, MQE supports multimodal community search on heterogeneous graphs with keyword and image queries. Secondly, to facilitate community understanding in real business scenarios, MQE generates natural language descriptions for the retrieved community in combination with other useful demographic information. The distinct features of MQE benefit many downstream applications in Alibaba’s e-commerce platform like recommendation. Our experiments confirm the effectiveness and efficiency of MQE on graphs with billions of edges.

Keywords

Community Search, Community Understanding, Multimodal Search, Text Generation

Discipline

Programming Languages and Compilers | Software Engineering

Research Areas

Intelligent Systems and Optimization

Publication

Proceedings of the 30th ACM International Conference on Information & Knowledge Management, Virtual Conference, 2021 November 1-5

First Page

1

Last Page

5

Identifier

10.1145/3459637.3481973

Publisher

ACM

City or Country

Virtual Conference

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