mlsanityData to 7 Oct 2026

AliMe MKG: A Multi-modal Knowledge Graph for Live-streaming E-commerce

arXiv 2109.07411 ↗First posted 13 Sep 2021cs.IR cs.AIcited by 8

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Abstract (arXiv)

Live streaming is becoming an increasingly popular trend of sales in E-commerce. The core of live-streaming sales is to encourage customers to purchase in an online broadcasting room. To enable customers to better understand a product without jumping out, we propose AliMe MKG, a multi-modal knowledge graph that aims at providing a cognitive profile for products, through which customers are able to seek information about and understand a product. Based on the MKG, we build an online live assistant that highlights product search, product exhibition and question answering, allowing customers to skim over item list, view item details, and ask item-related questions. Our system has been launched online in the Taobao app, and currently serves hundreds of thousands of customers per day.

Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). Builds on 8 of its 8 references that are in the map. First posted on arXiv 13 Sep 2021.

Builds on

8 of 8 references.

References · 8

  1. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  2. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  3. 2020An Image is Worth 16x16 Words: Transformers for Image Recognition at Scalecited by 29,915
  4. 2020Pixel-BERT: Aligning Image Pixels with Text by Deep Multi-Modal Transformerscited by 288
  5. 2019StructBERT: Incorporating Language Structures into Pre-training for Deep Language Understandingcited by 108
  6. 2020FLAT: Chinese NER Using Flat-Lattice Transformercited by 67
  7. 2021LightningDOT: Pre-training Visual-Semantic Embeddings for Real-Time Image-Text Retrievalcited by 44
  8. 2020AliMe KG: Domain Knowledge Graph Construction and Application in E-commercecited by 16

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Cited by year

Citing papers per year: 2022: 3; 2023: 2; 2024: 1; 2025: 2.

8 papers.