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引入文本語義信息的上市公司風險智能識別 版權信息
- ISBN：9787518999675
- 條形碼：9787518999675 ; 978-7-5189-9967-5
- 裝幀：簡裝本
- 冊數：暫無
- 重量：暫無
- 所屬分類：>
引入文本語義信息的上市公司風險智能識別 本書特色
本書將多種類型的非結構化文本數據以及多種智能化的手段運用于上市公司風險識別研究中，采用綜合集成的思路，綜合運用計算機科學、管理科學與工程、金融學、情報學、人工智能、決策支持系統、系統工程和軟件工程等多個學科和領域的多種方來識別上市公司的風險，為決策者提供智能化的決策支持。本書可為從事金融科技、金融數據分析、文本挖掘、數據分析、情報服務等領域的研究人員和技術人員提供參考。
引入文本語義信息的上市公司風險智能識別 內容簡介
本書將多種類型的非結構化文本數據以及多種智能化的手段運用于上市公司風險識別研究中，采用綜合集成的思路，綜合運用計算機科學、管理科學與工程、金融學、情報學、人工智能、決策支持系統、系統工程和軟件工程等多個學科和領域的多種方法、技術來識別上市公司的風險，為決策者提供智能化的決策支持。本書可為從事金融科技、金融數據分析、文本挖掘、數據分析、情報服務等領域的研究人員和技術人員提供參考。
引入文本語義信息的上市公司風險智能識別 目錄
目 錄 1 引 言 ···················································································1 1.1 研究背景及意義 ·································································1 1.2 國內外研究現狀分析 ···························································5 1.3 研究內容、方法、思路與創新 ·············································· 2 理論基礎與模型框架 ·····························································26 2.1 上市公司風險與上市公司風險識別 ········································26 2.2 知識工程與機器學·························································34 2.3 文本語義信息及其挖掘方法 ·················································48 2.4 數據驅動的管理決策與數據資源的特征分析 ····························54 2.5 系統工程方與霍爾三維結構 ···········································57 2.6 上市公司風險智能識別模型框架的構建 ··································59 3 上市公司風險因素智能感知 ···················································67 3.1 研究問題的分析與描述 ·······················································67 3.2 基于短語挖掘的上市公司風險因素智能感知模型 ······················68 3.3 上市公司風險因素數據與實驗數據采集 ··································70 3.4 上市公司風險因素短語的抽取 ··············································73 3.5 基于上市公司風險因素短語的知識利用 ··································79 4 上市公司風險事件智能監測 ···················································89 4.1 研究問題的分析與描述 ·······················································89 4.2 基于主題摘要的上市公司風險事件智能監測模型 ······················90 4.3 上市公司風險事件監測數據與實驗數據采集 ····························92 4.4 金融情感詞典的構建與上市公司風險事件文本數據的提取 ··········94 4.5 上市公司風險事件主題摘要的生成與自動推送 ·······················108 5 上市公司風險事件智能預測 ·················································1 5.1 研究問題的分析與描述 ·····················································1 5.2 基于本體推理的上市公司風險事件智能預測模型 ····················121 5.3 上市公司風險事件預測數據與實驗數據采集 ··························123 5.4 上市公司風險事件預測本體知識庫的構建 ·····························130 5.5 基于本體知識推理的上市公司風險事件預測 ··························145 6 結與展望 ·········································································153 6.1 研結 ·······································································153 6.2 研究展望 ·······································································155 參考文獻 ··················································································157 附錄 本書形成的可復用的知識資源 ·········································177
展開全部
引入文本語義信息的上市公司風險智能識別 作者簡介
譚明亮，川北醫學院管理學院講師，武漢大學管理學博士，研究方向為智能系統與情報服務。近五年，在《情報學報》《情報理論與實踐》《信息資源管理學報》《情報科學》《圖書與情報》《Journal of Forecasting》《The Electronic Library》等CSSCI/SSCI核心期刊上文10篇，參與國家社會科學重大項目、國家自然科學項目等5項課題。
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