AliCoCo: Alibaba E-commerce Cognitive Concept Net

By Xusheng Luo, Luxin Liu, Yonghua Yang, Le Bo, Yuanpeng Cao, Jinhang Wu, Qiang Li, Keping Yang, Kenny Q. Zhu. 2020

74 citations recorded by the source corpus.

One of the ultimate goals of e-commerce platforms is to satisfy various shopping needs for their customers. Much efforts are devoted to creating taxonomies or ontologies in e-commerce towards this goal. However, user needs in e-commerce are still not well defined, and none of the existing ontologies has the enough depth and breadth for universal user needs understanding. The semantic gap in-between prevents shopping experience from being more intelligent. In this paper, we propose to construct a large-scale E-commerce Cognitive Concept Net named "AliCoCo", which is practiced in Alibaba, the largest Chinese e-commerce platform in the world. We formally define user needs in e-commerce, then conceptualize them as nodes in the net. We present details on how AliCoCo is constructed semi-automatically and its successful, ongoing and potential applications in e-commerce.

Subfields: Artificial Intelligence, Information Systems

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Han-Jia Ye
2. De-chuan Zhan
3. Da-Wei Zhou
4. Fu-Yun Wang
5. Yong Li
6. Chen Gao
7. Depeng Jin
8. Xiangnan He

In Information Systems

1. Yong Li
2. Chen Gao
3. Depeng Jin
4. Xiangnan He
5. Yu Zheng
6. Jianxin Chang
7. Nian Li
8. Jinghua Piao

Citations in the corpus

• PyCIL: a Python toolbox for class-incremental learning (2021, background): “For example, when training a robot in the open-world, it meets new objects as time goes, and in the electronic commerce platform, new types of products appear daily (Luo et al., 2020; Xu et al., 2019).”
• A Survey of Graph Neural Networks for Recommender Systems: Challenges, Methods, and Directions (2021, background): “In addition, in e-commerce platform, products may have rich attributes, such as price [244], category [248], etc., based on which heterogeneous graphs can be constructed [117].”