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Jingdong book

中文问答系统技术及应用

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Jingdong book

中文问答系统技术及应用

Name: 中文问答系统技术及应用
Brand: Jingdong book
SKU: 3118183181
Price: 44.38 USD
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Content Description

本书全面系统地介绍问答系统的基本技术及应用，不仅讨论受限领域的问答系统，而且讨论开放领域的问答系统。全书共13章，第1章为绪论，介绍问答系统的研究背景、意义、研究现状及分类，然后分为两个部分，分别介绍受限域问答系统和开放域问答系统。在受限域问答系统中，讨论面向常问问题库及面向本体的问答策略，并讨论推理机制在问答系统中的应用。在开放域问答系统中，讨论中文问题分类技术及关键词扩展技术，然后讨论大规模问答对库的建立、答案推荐的技术等。各章对理论的叙述力求概念清晰、表达准确，突出理论联系实际，富有启发性，易于理解。
本书可以作为高等学校自然语言处理和计算语言学等专业本科生和研究生自然语言处理的教材，也可以作为从事自然语言处理相关领域的研究人员和技术人员的参考书。

Author Description

张巍，山西职工医学院副教授，中国计算机学会会员，山西省计算机学会会员，《软件导刊》编委会编委。荣获2011-2012学年学校十佳教师；2014-2015学年学校十佳教师。主讲Web系统与技术、无线网络通信技术、计算机应用基础、Visual Basic程序设计、网络数据库等课程。

Catalogue

目录
第1章绪论 1
1．1 中文问答系统研究 1
1．1．1 研究背景 1
1．1．2 研究意义 2
1．2 问答系统国内外研究现状 3
1．3 问答系统的分类 4
第一部分受限域问答系统
第2章受限域问答系统及本体 10
2．1 本书受限域问答系统研究内容 10
2．2 本书第一部分结构 11
2．3 本体语言简介 12
2．3．1 本体的概念 12
2．3．2 本体描述语言OWL 12
2．4 “医院”领域本体的构建 13
2．4．1 医学知识的特点 13
2．4．2 利用Protégé构建“医院”领域本体 14
2．5 实验及结果分析 17
2．5．1 本体构建实验 17
2．5．2 本体推理实验――阿莫西林与抗感染药推理过程 19
2．5．3 实验结果分析 19
第3章面向FAQ库的问答策略 23
3．1 问题库的建设 23
3．2 基于常问问题集的问答策略分析 25
3．2．1 索引表的建立 25
3．2．2 句子相似度计算策略1―基于统计和语义的方法 25
3．2．3 句子相似度计算策略2―基于依存句法和改进编辑距离的方法 29
3．2．4 FAQ库的更新 31
3．3 实验及结果分析 32
3．3．1 实验评测标准 32
3．3．2 实验结果及分析 32
第4章面向本体知识库的问答策略 36
4．1 本体知识库问答模块概述 36
4．2 问句浅层语义分析 37
4．2．1 语义块定义规则 37
4．2．2 问句向量 41
4．2．3 语义块的判定 42
4．2．4 语义块冲突的处理 42
4．3 问句处理实验结果及分析 43
4．4 本体查询模块答案的抽取 44
4．5 实验及结果分析 46
4．6 面向本体知识库的问答策略的不足与展望 47
第5章 Jena推理及在问答系统中的应用 48
5．1 推理机研究 48
5．1．1 推理机的功能 48
5．1．2 本体推理机 48
5．2 Jena研究 50
5．2．1 Jena及其结构 50
5．2．2 Jena2推理机 51
5．3 实验设计及实现 52
5．3．1 Jena推理实验一 52
5．3．2 Jena推理实验二 54
5．3．3 实验结果分析 55
第6章 SWRL及Jess推理在问答系统中的应用 56
6．1 SWRL架构及表示方式 56
6．2 基于本体的SWRL及Jess推理系统框架 57
6．3 推理系统的实现框架 58
6．4 推理过程 58
6．4．1 SWRL规则的建立 58
6．4．2 SWRL规则及OWL本体知识转换 61
6．5 实验及结果分析 61
6．5．1 在Protégé 3．4．1环境下的实验 61
6．5．2 在MyEclipse环境下的实验 63
6．5．3 实验结果分析 65
第7章城域医院问答检索系统的实现 66
7．1 系统的构建意义 66
7．2 系统设计原则 66
7．3 系统总体结构 66
7．4 系统实现与分析 67
第二部分开放域问答系统
第8章开放域问答系统概述 72
8．1 开放域问答系统的特点 72
8．2 开放域问答系统的基本结构 72
8．3 本书第二部分结构 73
第9章基于语义特征的中文问题分类方法 75
9．1 知网简介 75
9．2 问题的表示 77
9．3 问题预处理和关键词提取 78
9．4 问题分类特征的选取与表示 79
9．4．1 问题疑问词的提取 79
9．4．2 问题的核心关键词在《知网》中的主要义原的提取 80
9．4．3 命名实体的提取 84
9．4．4 单/复数的提取 84
9．4．5 问句分类特征的向量表示 85
9．5 问题分类算法 85
9．5．1 支持向量机 85
9．5．2 KNN算法 88
9．5．3 最大熵算法 89
9．6 问题分类体系 90
9．7 中文问题分类实验 90
9．7．1 实验方案 90
9．7．2 实验数据 91
9．7．3 评价标准 92
9．7．4 实验结果和实验分析 92
第10章基于同义词词林和知网的关键词扩展 95
10．1 关键词扩展的意义 95
10．2 信息检索中的同义词 96
10．3 同义词词林及其扩展版 97
10．4 基于知网的词语相似度计算 98
10．5 利用《同义词词林》扩展，利用《知网》精简的关键词扩展 99
10．6 实验结果及其讨论 100
10．6．1 同义词扩展实验 100
10．6．2 扩展查询实验 101
第11章答案源的获取方法研究 102
11．1 网页采集 102
11．2 网页去重 106
11．2．1 网页的预处理 106
11．2．2 网页去重的处理方法 107
11．2．3 网页去重算法测评 111
11．3 信息提取 111
11．3．1 网页净化 111
11．3．2 DOM树的概念 112
11．3．3 模糊归类算法 113
11．3．4 节点影响度因子 114
11．3．5 算法综述 114
11．3．6 实验设计与结果 115
11．4 基于百度知道的问答对库的建立 117
11．4．1 百度知道问答社区简介 117
11．4．2 建立基于关系模式的问答对库 119
第12章基于大规模问答对库的答案推荐 121
12．1 研究背景和研究现状 121
12．2 问题相似度计算方法 122
12．2．1 基于向量空间的TF-IDF句子相似度计算方法 123
12．2．2 基于关键词语义的句子相似度计算方法 123
12．2．3 基于语义依存的句子相似度计算方法 124
12．3 实验过程及结果分析句子相似度计算的评价 125
12．3．1 实验数据 125
12．3．2 实验方法及结果 125
第13章基于相似问题推荐的问答系统原型 127
13．1 基于相似问题推荐的问答系统技术路线 127
13．2 基于相似问题推荐的问答系统原型结构图 127
13．3 原型系统工作方式 128
附录A 中文问题分类标准 130
附录B 百度知道的分类体系 132
附录C 知网与ICTCLAS词性标注方式比较 133
附录D 哈尔滨工业大学的依存句法分析中的句法关系 134
附录E 知网义原树的组成 135
附录F 知网知识词典中特殊符号的含义 136
参考文献 137

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