商业智能

定　　价：98 元

丛书名：数字经济专业系列教材

• 作者：肖升生
• 出版时间：2025/7/1
• ISBN：9787121508165
• 出 版 社：电子工业出版社

• 中图法分类：F713.51 
• 页码：400
• 版次：01
• 开本：16开

内容简介

本书从商业智能的基本概念、发展历程，到方法和技术进行深入探讨，详细介绍了各行业的具体应用，内容全面覆盖了商业智能的关键领域。读者通过本书可系统学习数据整合、数据预处理、数据可视化、数据挖掘、文本挖掘、时空数据挖掘、社会网络分析等方面的知识。本书还结合前沿技术进行具体分析，如基于多模态大模型的商业智能和可信人工智能，以保持与行业最新趋势的同步。此外，本书还特别关注数字营销、数字财务与审计、数字金融、数字人力资源管理等实际应用领域，让读者在掌握核心概念的同时，了解如何将所学理论知识有效地运用于实践。

作者介绍

肖升生，上海财经大学数字经济学院副院长，副教授、博士生导师。研究关注数据挖掘、机器学习、人工智能等新兴数字智能技术在经济和社会管理中的应用。尤其关注数字金融平台服务策略设计、数智供应链金融与风险管控、平台经济与管理、AI算法的公平及有效性等。研究成果发表在经济管理一流国际期刊上。主持国家自然科学基金项目、教育部优秀青年培育项目、上海汽车工业教育基金会项目、上海市教改项目，并先后参与多项国家/省部级研究课题和校企商务智能项目。其中，已结题的国家自然科学青年项目获基金委管理学部绩效评估"优秀”评价。荣获 2022年度上海市科技进步奖二等奖，2020年度上海财经大学教学成果一等奖，上海财经大学第二届青年教师教学竞赛三等奖，2017/2019/2021/2022年荣获上海财经大学优秀本科毕业论文指导教师。受邀担任上海金融科技产业联盟智慧金融专业委员会委员，PACIS等国际会议。担任Associate Editor, ISR、DSS、I&M等国际一流期刊审稿人。

目 录

第1 篇 商业智能基础：基本概念和流程
第1 章 商业智能概述····································································································.2
1.1 商业智能的基本概念··························································································.2
1.1.1 商业智能的定义······················································································.2
1.1.2 数据、信息和知识之间的关系····································································.2
1.2 商业智能的发展历程··························································································.3
1.3 商业智能的系统架构与关键技术···········································································.4
1.3.1 商业智能的系统架构················································································.4
1.3.2 商业智能的关键技术················································································.5
1.4 商业智能的应用场景与系统/工具··········································································.8
1.4.1 商业智能的应用场景················································································.8
1.4.2 商业智能的系统/工具··············································································.11
1.5 商业智能的发展趋势与挑战················································································.13
1.5.1 商业智能的发展趋势···············································································.13
1.5.2 商业智能面临的挑战···············································································.14
本章小结··············································································································.15
课后习题··············································································································.15
参考文献··············································································································.15
第2 篇 商业智能方法和技术
第2 章 数据整合：数据仓库和OLAP ··············································································.18
2.1 数据仓库概述·································································································.18
2.1.1 数据仓库的起源与发展············································································.18
2.1.2 数据仓库及相关概念···············································································.24
2.1.3 数据仓库的体系结构与实现过程································································.28
2.2 数据仓库的相关技术·························································································.31
2.2.1 多维数据模型··························································································31
2.2.2 ETL ······································································································35
2.2.3 OLAP····································································································38
2.3 OLAP 详解······································································································39
2.3.1 基本概念································································································39
2.3.2 数据立方体·····························································································42
2.3.3 多维数据分析··························································································46
2.4 OLAP 的体系结构、建模方法、实现过程和产品······················································49
2.4.1 OLAP 的体系结构····················································································49
2.4.2 维度建模································································································52
2.4.3 OLAP 的实现过程和产品···········································································56
2.5 综合案例·········································································································58
2.5.1 数据仓库的搭建·······················································································59
2.5.2 OLAP 的实现··························································································64
2.5.3 数据挖掘································································································66
本章小结···············································································································66
课后习题···············································································································66
参考文献···············································································································67
第3 章 数据预处理与数据可视化·····················································································69
3.1 数据预处理的必要性··························································································69
3.2 数据预处理方法································································································70
3.2.1 数据清洗································································································70
3.2.2 数据转换································································································78
3.2.3 数据特征提取··························································································84
3.3 数据可视化简介································································································92
3.3.1 数据可视化的定义和作用···········································································92
3.3.2 商业智能与数据可视化··············································································93
3.4 数据可视化方法································································································94
3.4.1 数据可视化的常用统计图表········································································94
3.4.2 交互式数据可视化工具···········································································.104
本章小结············································································································.106
课后习题············································································································.106
参考文献············································································································.107
第4 章 数据挖掘·········································································································109
4.1 数据挖掘概述·································································································109
4.2 分类分析·······································································································110
4.2.1 基本概念······························································································110
4.2.2 决策树·································································································111
4.2.3 集成分类器···························································································114
4.2.4 其他分类方法························································································117
4.2.5 分类性能的度量指标···············································································118
4.3 关联分析·······································································································120
4.3.1 基本概念······························································································120
4.3.2 关联规则生成算法··················································································122
4.3.3 关联规则评估指标··················································································124
4.3.4 关联分析的高级方法与策略······································································125
4.4 聚类分析·······································································································125
4.4.1 基本概念······························································································125
4.4.2 样本之间距离的计算···············································································126
4.4.3 聚类算法与模型·····················································································128
4.4.4 性能评价······························································································132
4.5 数据挖掘中的伦理和隐私保护问题·······································································135
4.5.1 数据挖掘中的伦理问题············································································135
4.5.2 数据挖掘中的隐私保护问题······································································135
4.5.3 相关法律法规························································································136
本章小结··············································································································136
课后习题··············································································································137
参考文献··············································································································137
第5 章 文本挖掘·········································································································140
5.1 文本挖掘概述·································································································140
5.1.1 文本挖掘的基本概念···············································································140
5.1.2 文本挖掘面临的挑战···············································································141
5.1.3 文本挖掘的应用场景···············································································143
5.2 文本预处理····································································································143
5.2.1 文本词条化···························································································144
5.2.2 文本规范化···························································································146
5.2.3 噪声去除······························································································149
商业智能
X
5.3 文本表示······································································································.152
5.3.1 文本离散式表示····················································································.152
5.3.2 文本概念表示·······················································································.155
5.3.3 文本深度表示·······················································································.158
5.4 文本分析和知识发现·······················································································.162
5.4.1 文本分类·····························································································.162
5.4.2 文本聚类·····························································································.163
5.4.3 信息提取·····························································································.164
本章小结············································································································.165
课后习题············································································································.165
参考文献············································································································.165
第6 章 时空数据挖掘·································································································.169
6.1 时空数据挖掘概述··························································································.169
6.1.1 基本概念·····························································································.169
6.1.2 应用场景·····························································································.171
6.1.3 典型实际应用·······················································································.174
6.2 时空数据管理································································································.176
6.2.1 时空索引·····························································································.176
6.2.2 轨迹数据管理·······················································································.179
6.3 时间序列预测方法··························································································.183
6.3.1 传统时序建模方法·················································································.184
6.3.2 机器学习建模方法·················································································.186
6.3.3 深度学习建模方法·················································································.187
6.4 时空数据挖掘算法··························································································.187
6.4.1 空间数据可视化····················································································.187
6.4.2 时空数据统计·······················································································.190
6.4.3 典型的时空数据挖掘算法········································································.192
本章小结············································································································.196
课后习题············································································································.196
参考文献············································································································.197
第7 章 社会网络分析·································································································.199
7.1 社会网络概述································································································.199
7.1.1 社会网络简介·······················································································.199
7.1.2 社会网络的基本概念··············································································.200
目 录
XI
7.1.3 社会网络研究的经典案例·········································································205
7.2 社会网络模型·································································································207
7.2.1 社会网络模型与真实世界网络···································································207
7.2.2 ER 随机图模型·······················································································209
7.2.3 WS 小世界网络模型················································································211
7.2.4 BA 无标度网络模型················································································212
7.3 社群发现·······································································································213
7.3.1 社群的基本概念·····················································································213
7.3.2 模块度·································································································214
7.3.3 基于成员与图连接的社群发现···································································214
7.3.4 社群发现算法························································································215
7.4 影响力和中心性······························································································217
7.4.1 影响力·································································································217
7.4.2 中心性·································································································218
7.5 社会网络中的信息传播······················································································221
7.5.1 信息传播的基本概念···············································································221
7.5.2 传播动力学···························································································222
7.5.3 社会网络信息传播研究············································································224
本章小结··············································································································226
课后习题··············································································································226
参考文献··············································································································227
第3 篇 商业智能应用
第8 章 数字营销·········································································································230
8.1 数字营销概述·································································································230
8.1.1 数字营销的定义·····················································································230
8.1.2 数字营销的主要方式···············································································231
8.1.3 数字营销的优势·····················································································233
8.2 面向数字营销的用户画像···················································································234
8.2.1 用户画像概述························································································234
8.2.2 用户画像与精准营销···············································································236
8.2.3 案例分析：去哪儿网用户画像的构建与应用·················································238
8.3 数字平台营销推荐服务······················································································241
8.3.1 推荐系统······························································································241
8.3.2 基于内容的推荐算法···············································································243
8.3.3 基于近邻的协同过滤算法········································································.244
8.3.4 基于矩阵分解的协同过滤算法··································································.246
8.4 AIGC 时代的数字营销·····················································································.248
8.4.1 AIGC 概述··························································································.248
8.4.2 AIGC 与数字营销··················································································.249
本章小结············································································································.250
课后习题············································································································.250
参考文献············································································································.251
第9 章 数字财务与审计······························································································.253
9.1 数字财务与审计概述·······················································································.253
9.1.1 数字财务概述·······················································································.253
9.1.2 数字审计概述·······················································································.257
9.2 财务和审计数字化转型····················································································.263
9.2.1 财务数字化转型····················································································.263
9.2.2 审计数字化转型····················································································.269
9.2.3 案例：见知公司的自动对账系统·······························································.272
9.3 智能财务的应用：大数据预算管理·····································································.275
9.3.1 预算管理概述·······················································································.275
9.3.2 预算管理中的智能技术···········································································.276
9.3.3 案例分析：韩都衣舍的大数据预算管理······················································.276
9.4 智能审计的应用：财务欺诈识别········································································.279
9.4.1 财务欺诈概述·······················································································.279
9.4.2 常见的财务欺诈识别技术········································································.281
9.4.3 案例分析：康美药业财务舞弊··································································.282
本章小结············································································································.287
课后习题············································································································.287
参考文献············································································································.287
第10 章 数字金融······································································································.289
10.1 数字金融概述······························································································.289
10.1.1 数字金融的发展背景和基本概念·····························································.289
10.1.2 数字金融的作用和典型应用场景·····························································.290
10.1.3 数字金融发展面临的挑战······································································.292
10.2 数字金融在供应链金融领域的应用···································································.294
10.2.1 资金流动性管理···························295
10.2.2 信用评估与风险控制··············································································295
10.2.3 案例分析：阿里巴巴通过SWIFT 全球支付创新服务优化供应链金融·················296
10.3 数字金融在不动产估值领域的应用·····································································297
10.3.1 传统估值方法·······················································································298
10.3.2 智能估值方法·······················································································299
10.3.3 案例分析：Zillow 运用不动产智能估值开展即时买卖业务失败························301
本章小结··············································································································303
课后习题··············································································································303
参考文献··············································································································303
第11 章 数字人力资源管理···························································································306
11.1 数字人力资源管理概述····················································································306
11.1.1 数字人力资源管理的定义和范围·······························································306
11.1.2 数字人力资源管理的演进趋势··································································307
11.1.3 商业智能如何支持数字人力资源管理·························································309
11.2 商业智能与人才招聘·······················································································310
11.2.1 人才精准画像·······················································································310
11.2.2 人岗匹配预测·······················································································312
11.2.3 自动化人才评估····················································································313
11.3 商业智能与人才培养·······················································································314
11.3.1 个性化培训推荐····················································································314
11.3.2 高潜力员工识别····················································································315
11.3.3 人才团队建设·······················································································316
11.4 商业智能与人才发展·······················································································316
11.4.1 工作绩效预测·······················································································317
11.4.2 工作满意度预测····················································································317
11.4.3 职业流动性预测····················································································318
本章小结··············································································································319
课后习题··············································································································319
参考文献··············································································································319
第4 篇 前沿主题
第12 章 商业智能与大模型···························································································327
12.1 大语言模型···································································································327
12.1.1 基本概念·····························································································327
12.1.2 大语言模型的发展历程···········································································330
12.1.3 经典大语言模型概述············································································.331
12.1.4 大语言模型的应用风险与挑战································································.334
12.2 多模态数据与多模态大模型············································································.336
12.2.1 多模态数据························································································.336
12.2.2 多模态大模型·····················································································.337
12.2.3 多模态大模型是人工智能大模型发展的方向··············································.339
12.3 大模型在商业智能中的应用············································································.341
12.3.1 大模型在商业智能中应用的关键步骤·······················································.341
12.3.2 大模型在商业智能中的典型应用领域·······················································.342
12.3.3 大模型在商业智能中的应用趋势与挑战····················································.345
本章小结············································································································.347
课后习题············································································································.348
参考文献············································································································.348
第13 章 可信人工智能································································································.350
13.1 可解释人工智能···························································································.350
13.1.1 可解释性概述·····················································································.351
13.1.2 本质可解释方法详述············································································.354
13.1.3 事后可解释方法详述············································································.357
13.1.4 模型可解释性技术的应用领域································································.363
13.2 人工智能隐私安全························································································.366
13.2.1 数据隐私和保护··················································································.366
13.2.2 模型安全与攻击防护············································································.367
13.2.3 案例分析：网络中的链路窃取攻防··························································.368
13.2.4 案例分析：针对机器学习模型的成员推测攻防···········································.374
本章小结············································································································.381
课后习题············································································································.381
参考文献·············································································································