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AliCoCo: Alibaba E-commerce Cognitive Concept Net

arXiv 2003.13230 ↗First posted 30 Mar 2020cs.IR cs.CLcited by 23

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Abstract (arXiv)

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.

Key facts. Cited by 23 papers in the map (data through 7 Oct 2026). First posted on arXiv 30 Mar 2020.

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Citing papers per year: 2021: 8; 2022: 4; 2023: 3; 2024: 4; 2025: 1; 2026: 3.

23 papers.

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  1. 2021PyCIL: A Python Toolbox for Class-Incremental Learningcited by 83
  2. 2021Co-Transport for Class-Incremental Learningcited by 38
  3. 2022FolkScope: Intention Knowledge Graph Construction for E-commerce Commonsense Discoverycited by 23
  4. 2022Rethinking Graph Convolutional Networks in Knowledge Graph Completioncited by 20
  5. 2023Vision, Deduction and Alignment: An Empirical Study on Multi-modal Knowledge Graph Alignmentcited by 19
  6. 2021Enquire One's Parent and Child Before Decision: Fully Exploit Hierarchical Structure for Self-Supervised Taxonomy Expansioncited by 13
  7. 2022Construction and Applications of Billion-Scale Pre-Trained Multimodal Business Knowledge Graphcited by 13
  8. 2021K-PLUG: Knowledge-injected Pre-trained Language Model for Natural Language Understanding and Generation in E-Commercecited by 12
  9. 2021Recommender systems based on graph embedding techniques: A comprehensive reviewcited by 8
  10. 2023Causality-aware Concept Extraction based on Knowledge-guided Promptingcited by 8
  11. 2024Intention Knowledge Graph Construction for User Intention Relation Modelingcited by 6
  12. 2022Learning What You Need from What You Did: Product Taxonomy Expansion with User Behaviors Supervisioncited by 4
11 more
  1. 2024FLAME: Self-Supervised Low-Resource Taxonomy Expansion using Large Language Modelscited by 4
  2. 2024Branch-Tuning: Balancing Stability and Plasticity for Continual Self-Supervised Learningcited by 4
  3. 2021Automatic Product Ontology Extraction from Textual Reviewscited by 2
  4. 2025GSID: Generative Semantic Indexing for E-Commerce Product Understandingcited by 2
  5. 2026TaxoBell: Gaussian Box Embeddings for Self-Supervised Taxonomy Expansioncited by 2
  6. 2021TAG: Toward Accurate Social Media Content Tagging with a Concept Graphcited by 1
  7. 2021Intent-based Product Collections for E-commerce using Pretrained Language Modelscited by 1
  8. 2023A Concept Knowledge Graph for User Next Intent Prediction at Alipaycited by 1
  9. 2026AutoPKG: An Automated Framework for Dynamic E-commerce Product-Attribute Knowledge Graph Constructioncited by 1
  10. 2024A Utility-Mining-Driven Active Learning Approach for Analyzing Clickstream Sequencescited by 0
  11. 2026JD Oxygen AI Item Center (Oxygen AIIC) V1: An Industrial-Scale LLM/VLM-Centric Solution for Item Understanding, Management, and Applicationscited by 0