这是一本全面讲解图计算、知识图谱及其在推荐系统领域应用的专著，为读者基于神经网络构建推荐系统提供了详细指导，是作者在相关领域10余年经验的总结。掌握本书内容，读者可开发出能处理多模态数据的推荐系统，提供更丰富和准确的推荐体验。本书主要内容分为两篇。 第一篇图数据以及图模型（第1-3章） 对图数据、图神经网络、知识图谱的基础知识进行了梳理，帮助读者掌握这3项技术的关键原理与算法，为后面的学习打下基础。 第二篇推荐系统（第4-9章） 首先介绍了推荐系统的架构，包括逻辑架构、技术架构和数据建模，以及基于GNN的推荐系统架构；然后详细讲解了如何基于GNN构建推荐系统，以及基于图的推荐算法；接着讲解了知识图谱在推荐系统中的应用以及相关的算法模型；最后探讨了推荐系统领域当前的热点问题、研究方向，以及工业级推荐系统领域的核心难题。

Contents..目　　录
推荐序一
推荐序二
推荐序三
前言
第一篇 图数据与图模型
第1章 图数据基础 ··························2
1.1 数学基础 ·····································2
1.2 图的基本知识 ······························4
1.2.1.什么是图 ·························4
1.2.2.图中基本元素及定义 ·········5
1.3 图的表示方法 ····························10
1.3.1.图的代数表示 ················11
1.3.2.图的遍历 ·······················13
1.4 图数据及图神经网络 ··················14　
1.4.1.图数据的性质 ················14
1.4.2.图数据应用 ···················15
1.4.3.图神经网络的发展史 ·······16
1.5 本章小结 ···································17
第2章 图神经网络基础 ·················18
2.1 神经网络的基本知识 ··················18
2.1.1.神经元 ··························19
2.1.2.前馈神经网络 ················22
2.1.3.反向传播 ·······················23
2.2 卷积神经网络 ····························24
2.2.1.卷积神经网络基本概念
和特点 ··························25
2.2.2.卷积神经网络模型 ··········29
2.3 循环神经网络 ····························30
2.3.1.循环神经网络结构和
特点 ·····························31
2.3.2.循环神经网络模型 ··········35
2.4 图神经网络 ································36
2.4.1.图神经网络综述 ·············36
2.4.2.卷积图神经网络 ·············41
2.4.3.循环图神经网络 ·············42
2.5 本章小结 ···································44
第3章 知识图谱基础 ·····················46
3.1 知识图谱的定义和模型 ···············46
3.1.1.知识图谱定义 ················47
3.1.2.知识图谱嵌入 ················48
3.1.3.距离变换模型 ················51
3.1.4.语义匹配模型 ················53
3.2 知识图谱上的神经网络 ···············55
3.2.1.关系图卷积网络 ·············55
3.2.2.知识图谱与注意力模型 ·····55
3.3 本章小结 ···································59