Publication Type

Conference Proceeding Article

Version

publishedVersion

Publication Date

5-2023

Abstract

In a globalized marketplace, one could access products or services from almost anywhere. However, resolving which product in one language corresponds to another product in a different language remains an under-explored problem. We explore this from two perspectives. First, given two products of different languages, how to assess their similarity that could signal a potential match. Second, given products from various languages, how to arrive at a multi-partite clustering that respects cardinality constraints efficiently. We describe algorithms for each perspective and integrate them into a promising solution validated on real-world datasets.

Keywords

Multi-lingual similarity, Multi-partite matching

Discipline

Databases and Information Systems

Research Areas

Data Science and Engineering

Publication

Proceedings of the World Wide Web Conference: WWW 2023

First Page

99

Last Page

102

ISBN

9781450394161

Identifier

10.1145/3543873.3587322

Publisher

ACM

City or Country

New York, USA

Additional URL

https://doi.org/10.1145/3543873.3587322

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