August 2022
Intermediate to advanced
441 pages
11h 26m
Chinese
Content preview from Python文本分析
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378
｜
第
12
章
12.7
关系提取
尽管共现图可以让我们对公司的网络关系有一些了解，但是我们并不知道这些
关系的类型。举个例子，在图
12-5
中，左上角的“
Schlumberger
”“
Fairchild
Semiconductor
”和“
Fujitsu
”等公司组成的子图。我们对这些公司之间的关系一无
所知，信息仍然隐藏在下面的句子中：
Fujitsu wants to expand. It plans to acquire 80% of Fairchild Corp, an industrial unit of
Schlumberger.
在本节中，我们将介绍两种基于模式的关系提取。第一种比较简单，即搜索
“
subject-predicate-object
”（主语
-
谓语
-
宾语）形式的短语。
第二种则使用句
子的句法结构（即依存树），获取更准确的结果，但使用的规则也更复杂。最
后，我们将生成基于四种关系的知识图：“
acquires
”“
sells
”“
subsidiary-of
”和
“
chairperson-of
”。老实说，为了便于识别，我们使用的“
acquires
”和“
sells
”
的定义比较宽泛。它们也可以匹配这样的句子：“
Fujitsu
plans to acquire 80%
of
Fairchild Corp
”，甚至是“
Fujitsu
withdraws the option to acquire
Fairchild Corp
”。
由于自然语言的歧义以及关系的诸多种类与变化，关系提取是一个复杂的问题 ...
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I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.