Clothing recommendation method based on Neo4j knowledge graph

Clothing recommendation method based on Neo4j knowledge graph

The invention discloses a garment recommendation method based on a neo4j knowledge graph, and relates to the technical field of data processing, and a recommendation system uses a graph database, collaborative filtering, deep learning, character string similarity and other technologies to generate p...

Ausführliche Beschreibung

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Bibliographische Detailangaben
Hauptverfasser: ZHANG BINGJUE, ZHANG WEI, DAI GUOJUN
Format: Patent
Sprache:chi ; eng
Schlagworte:
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES
ELECTRIC DIGITAL DATA PROCESSING
PHYSICS
SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR
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Beschreibung
Zusammenfassung:The invention discloses a garment recommendation method based on a neo4j knowledge graph, and relates to the technical field of data processing, and a recommendation system uses a graph database, collaborative filtering, deep learning, character string similarity and other technologies to generate personalized recommendation. This combination maintains efficiency when processing highly connected data and enables learning of complex patterns to improve the accuracy of recommendations. 本发明为基于neo4j知识图谱的服装推荐方法，涉及数据处理技术领域，推荐系统使用了图数据库，协同过滤，深度学习和字符串相似度等技术来生成个性化的推荐。这种组合在处理高度连接的数据时保持效率，并能够学习复杂的模式来提高推荐的准确性。