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引入文本语义信息的上市公司风险智能识别

引入文本语义信息的上市公司风险智能识别

1星价 ¥33.6 (7.0折)
2星价¥33.6 定价¥48.0
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  • ISBN:9787518999675
  • 装帧:简裝本
  • 册数:暂无
  • 重量:暂无
  • 开本:16开
  • 页数:196
  • 出版时间:2023-02-01
  • 条形码:9787518999675 ; 978-7-5189-9967-5

本书特色

本书将多种类型的非结构化文本数据以及多种智能化的手段运用于上市公司风险识别研究中,采用综合集成的思路,综合运用计算机科学、管理科学与工程、金融学、情报学、人工智能、决策支持系统、系统工程和软件工程等多个学科和领域的多种方来识别上市公司的风险,为决策者提供智能化的决策支持。本书可为从事金融科技、金融数据分析、文本挖掘、数据分析、情报服务等领域的研究人员和技术人员提供参考。

内容简介

本书将多种类型的非结构化文本数据以及多种智能化的手段运用于上市公司风险识别研究中,采用综合集成的思路,综合运用计算机科学、管理科学与工程、金融学、情报学、人工智能、决策支持系统、系统工程和软件工程等多个学科和领域的多种方法、技术来识别上市公司的风险,为决策者提供智能化的决策支持。本书可为从事金融科技、金融数据分析、文本挖掘、数据分析、情报服务等领域的研究人员和技术人员提供参考。

目录

目 录 1 引 言 ···················································································1 1.1 研究背景及意义 ·································································1 1.2 国内外研究现状分析 ···························································5 1.3 研究内容、方法、思路与创新 ·············································· 2 理论基础与模型框架 ·····························································26 2.1 上市公司风险与上市公司风险识别 ········································26 2.2 知识工程与机器学·························································34 2.3 文本语义信息及其挖掘方法 ·················································48 2.4 数据驱动的管理决策与数据资源的特征分析 ····························54 2.5 系统工程方与霍尔三维结构 ···········································57 2.6 上市公司风险智能识别模型框架的构建 ··································59 3 上市公司风险因素智能感知 ···················································67 3.1 研究问题的分析与描述 ·······················································67 3.2 基于短语挖掘的上市公司风险因素智能感知模型 ······················68 3.3 上市公司风险因素数据与实验数据采集 ··································70 3.4 上市公司风险因素短语的抽取 ··············································73 3.5 基于上市公司风险因素短语的知识利用 ··································79 4 上市公司风险事件智能监测 ···················································89 4.1 研究问题的分析与描述 ·······················································89 4.2 基于主题摘要的上市公司风险事件智能监测模型 ······················90 4.3 上市公司风险事件监测数据与实验数据采集 ····························92 4.4 金融情感词典的构建与上市公司风险事件文本数据的提取 ··········94 4.5 上市公司风险事件主题摘要的生成与自动推送 ·······················108 5 上市公司风险事件智能预测 ·················································1 5.1 研究问题的分析与描述 ·····················································1 5.2 基于本体推理的上市公司风险事件智能预测模型 ····················121 5.3 上市公司风险事件预测数据与实验数据采集 ··························123 5.4 上市公司风险事件预测本体知识库的构建 ·····························130 5.5 基于本体知识推理的上市公司风险事件预测 ··························145 6 结与展望 ·········································································153 6.1 研结 ·······································································153 6.2 研究展望 ·······································································155 参考文献 ··················································································157 附录 本书形成的可复用的知识资源 ·········································177
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作者简介

谭明亮,川北医学院管理学院讲师,武汉大学管理学博士,研究方向为智能系统与情报服务。近五年,在《情报学报》《情报理论与实践》《信息资源管理学报》《情报科学》《图书与情报》《Journal of Forecasting》《The Electronic Library》等CSSCI/SSCI核心期刊上文10篇,参与国家社会科学重大项目、国家自然科学项目等5项课题。

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