@inproceedings{swamy-etal-2025-address,
title = "An Address Intelligence Framework for {E}-commerce Deliveries",
author = "Swamy, Gokul and
Gulati, Aman and
Virinchi, Srinivas and
Saladi, Anoop",
editor = "Potdar, Saloni and
Rojas-Barahona, Lina and
Montella, Sebastien",
booktitle = "Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing: Industry Track",
month = nov,
year = "2025",
address = "Suzhou (China)",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.emnlp-industry.70/",
pages = "1026--1034",
ISBN = "979-8-89176-333-3",
abstract = "For an e-commerce domain, the customeraddress is the single most important pieceof customer data for ensuring accurateand reliable deliveries. In this two-partstudy, we first outline the construction ofa language model to assist customers withaddress standardization and in the latterpart, we detail a novel Pareto-ensemblemulti-task prediction algorithm that derives critical insights from customer addresses to minimize operational losses arising from a given geographical area. Finally, we demonstrate the potential benefits ofthe proposed address intelligence systemfor a large e-commerce domain throughlarge scale experiments on a commercialsystem."
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%0 Conference Proceedings
%T An Address Intelligence Framework for E-commerce Deliveries
%A Swamy, Gokul
%A Gulati, Aman
%A Virinchi, Srinivas
%A Saladi, Anoop
%Y Potdar, Saloni
%Y Rojas-Barahona, Lina
%Y Montella, Sebastien
%S Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing: Industry Track
%D 2025
%8 November
%I Association for Computational Linguistics
%C Suzhou (China)
%@ 979-8-89176-333-3
%F swamy-etal-2025-address
%X For an e-commerce domain, the customeraddress is the single most important pieceof customer data for ensuring accurateand reliable deliveries. In this two-partstudy, we first outline the construction ofa language model to assist customers withaddress standardization and in the latterpart, we detail a novel Pareto-ensemblemulti-task prediction algorithm that derives critical insights from customer addresses to minimize operational losses arising from a given geographical area. Finally, we demonstrate the potential benefits ofthe proposed address intelligence systemfor a large e-commerce domain throughlarge scale experiments on a commercialsystem.
%U https://aclanthology.org/2025.emnlp-industry.70/
%P 1026-1034
Markdown (Informal)
[An Address Intelligence Framework for E-commerce Deliveries](https://aclanthology.org/2025.emnlp-industry.70/) (Swamy et al., EMNLP 2025)
ACL
- Gokul Swamy, Aman Gulati, Srinivas Virinchi, and Anoop Saladi. 2025. An Address Intelligence Framework for E-commerce Deliveries. In Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing: Industry Track, pages 1026–1034, Suzhou (China). Association for Computational Linguistics.