Page 115 - AI for Good-Innovate for Impact Final Report 2024
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AI for Good-Innovate for Impact



               Use Case – 25: Enhancing SME Online Business through An

               Automatic Recommendation Powered by LLM and Knowledge
               Graph                                                                                                25-Ant Group












               Country: China

               Organization: Ant Group CO., Ltd.

               Contact person: Guanchen LIN, guanchen.lgc@ antgroup .com


               25�1� Use case summary table

                Domain         Business, economy

                The Prob-      •  Accelerate SMEs' ability to quickly find their customers under limited
                lem to be         resources.
                addressed      •  Ease the competitive relationship between SMEs (e.g., mini-program
                                  merchants) and large internet platforms.
                               •  Assist SMEs in implementing recommendation systems at a low cost to
                                  drive their revenue growth.

                Key aspects of  •  Structured knowledge representation: Ant Personalization Engine (APE)
                the solution      utilizes advanced NLP technologies including LLMs to create a universal
                                  knowledge graph, generates diverse entities from texts and logs, and
                                  establishes complex entity relationships using Entity-bert methods.
                               •  Multi-source heterogeneous knowledge understanding: APE devel-
                                  ops a multi-dimensional cold-start recommendation strategy using
                                  graph neural networks and knowledge transfer learning to address
                                  data sparsity and sample knowledge deficiency in long-tail scenes and
                                  private-domain scenarios, inspired by zero-shot and few-shot recommen-
                                  dation tasks in machine learning.
                               •  Cross-modal knowledge mining: APE establishes internal standards for
                                  content creation, explores generative techniques including stable diffu-
                                  sion (SD) model, LoRA, ControlNet, Roop, and iteratively enhances AIGC
                                  quality.
                               •  Machine Learning Operations (MLOps) Automation: APE provides SMEs
                                  with the capabilities for automated data integration, automated model
                                  training and deployment, as well as automated search and recommenda-
                                  tion.
                Technology     NLP, LLMs, Knowledge Graph, Cold-start Recommendations, AIGC, MLOps
                keywords

                Data availabil-  Private in Alipay
                ity

                Metadata (type  Structured and unstructured data
                of data)






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