[1]潘王蕾,何 瑛*.基于个性化推荐的服装知识图谱构建[J].服装学报,2022,7(03):275-282.
 PAN Wanglei,HE Ying*.Construction of Clothing Knowledge Graph Based onPersonalized Recommendation[J].Journal of Clothing Research,2022,7(03):275-282.
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基于个性化推荐的服装知识图谱构建()
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《服装学报》[ISSN:2096-1928/CN:32-1864/TS]

卷:
第7卷
期数:
2022年03期
页码:
275-282
栏目:
服装设计与营销
出版日期:
2022-06-30

文章信息/Info

Title:
Construction of Clothing Knowledge Graph Based onPersonalized Recommendation
作者:
潘王蕾1;  何 瑛*1; 2
1.浙江理工大学 服装学院,浙江 杭州 310018; 2.浙江理工大学 丝绸文化传承与产品设计数字化技术文化和旅游部重点实验室,浙江 杭州 310018
Author(s):
PAN Wanglei1;  HE Ying*1; 2
1. School of Fashion Design and Engineering,Zhejiang Sci-Tech University,Hangzhou 310018,China; 2. Key Laboratory of Silk Culture Inheriting and Products Design Digital Technology, Ministry of Culture and Tourism, Zhejiang Sci-Tech University,Hangzhou 310018,China
分类号:
TS 941.2
文献标志码:
A
摘要:
知识图谱作为大数据背景下信息承载及知识推理的工具,有助于解决大部分服装推荐系统中存在的用户和服装信息挖掘不全的问题。通过归纳服装个性化推荐的研究现状,对知识图谱及其相关实践应用进行概述,构建、分析服装领域知识体系,并将服装属性分为基础属性、表现属性和外在属性3个要素,其中服装外在属性中加入了以在线评论为基础,运用SnowNLP语言库得到的综合情感得分,并由此构建服装知识图谱,从中得到用户与服装、服装与服装之间的语义关系。通过连衣裙实例分析,证明知识图谱推理的可解释性,为服装个性化精准推荐提供参考。
Abstract:
As the information bearer and knowledge reasoning tool under the background of big data, knowledge graph is helpful to solve the problem that users and clothing information mining is not comprehensive enough in most clothing recommendation systems.This paper concluded the research present situation of clothing personalized recommendation,and summarized the knowledge graph and its application. It constructed and analyzed the knowledge system of clothing domain, and dividesd clothing attribute into three elements: basic attribute, performance attribute and external attribute. Among them, a comprehensive emotional score obtained by SnowNLP language library based on online comments was added to the external attributes of clothing, and the clothing knowledge graph was constructed to obtain the semantic relationship between users and clothing, clothing and clothing. This paper demonstrated the interpretability of knowledge graph inference through the example analysis of dress, and provided a reference for precise clothing personalized recommendation.

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更新日期/Last Update: 2022-06-30