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Home > Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence, 36 > No. 11: IAAI-22, EAAI-22, AAAI-22 Special Programs and Special Track, Student Papers and Demonstrations

Intelligent Online Selling Point Extraction for E-commerce Recommendation

February 1, 2023

Authors

Xiaojie Guo

JD.COM Silicon Valley Research Center


Shugen Wang

JD.COM


Hanqing Zhao

JD.COM


Shiliang Diao

JD.COM


Jiajia Chen

JD.COM


Zhuoye Ding

JD.COM


Zhen He

JD.COM


Jianchao Lu

JD.COM


Yun Xiao

JD.COM


Bo Long

JD.COM


Han Yu

Nanyang Technological University


Lingfei Wu

JD.COM Silicon Valley Research Center


Proceedings:

No. 11: IAAI-22, EAAI-22, AAAI-22 Special Programs and Special Track, Student Papers and Demonstrations

Volume

Issue:

Proceedings of the AAAI Conference on Artificial Intelligence, 36

Track:

IAAI Technical Track on Highly Innovative Applications of AI

Downloads:

Download PDF

Abstract:

In the past decade, automatic product description generation for e-commerce have witnessed significant advancement. As the services provided by e-commerce platforms become diverse, it is necessary to dynamically adapt the patterns of descriptions generated. The selling point of products is an important type of product description for which the length should be as short as possible while still conveying key information. In addition, this kind of product description should be eye-catching to the readers. Currently, product selling points are normally written by human experts. Thus, the creation and maintenance of these contents incur high costs. These costs can be significantly reduced if product selling points can be automatically generated by machines. In this paper, we report our experience developing and deploying the Intelligent Online Selling Point Extraction (IOSPE) system to serve the recommendation system in the JD.com e-commerce platform. Since July 2020, IOSPE has become a core service for 62 key categories of products (covering more than 4 million products). So far, it has generated more than 1.1 billion selling points, thereby significantly scaling up the selling point creation operation and saving human labour. These IOSPE generated selling points have increased the click-through rate (CTR) by 1.89% and the average duration the customers spent on the products by more than 2.03% compared to the previous practice, which are significant improvements for such a large-scale e-commerce platform.

DOI:

10.1609/aaai.v36i11.21501


AAAI

Proceedings of the AAAI Conference on Artificial Intelligence, 36



Topics: AAAI

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