User Interest Mapping Program
Steps to implement an e-commerce recommender system:
- Data preparation: Convert user behavior logs into
[用户, 行为类型, 商品, 时间戳]quaternion (math) - Atlas initialization::
graph.add_node(''User'', id=''U123'')Creating user nodes - dynamic update (Internet): By
graph.merge_edge()Methods to update user-item interaction weights in real time - semantic enhancement: for
浏览/收藏/购买Setting differentiated edge attributes for different behavior types such as
Query Example:MATCH (u:User)-[r:购买|浏览]->(p:Product) WHERE r.timestamp > date()-duration(''P7D'') RETURN pAccess to recent items of interest.
This answer comes from the articleGraphiti: dynamic knowledge graph construction and query tool (time-aware long memory scheme)The
May not be reproduced without permission:AI productivity tools " How can Graphiti be applied to build a user interest graph in a personalized recommendation scenario?
