例子:
doc1:I really liked my small dogs, and I think my mom also liked them.
doc2:He never liked any dogs, so I hope that my mom will not expect me to liked him.
分词,初步的倒排索引的建立 *表示有
word doc1 doc2
I * *
really *
liked * *
my * *
small *
dogs *
and *
think *
mom * *
also *
them *
He *
never *
any *
so *
hope *
that *
will *
not *
expect *
me *
to *
him *
演示了一下倒排索引最简单的建立的一个过程
搜索 mother like little dog,不可能有任何结果
mother
like
little
dog
搜索时会拆成这个四个词,一个一个区匹配找doucument。只要有一个就返回这个document 这里都没有,所以不可能有结果。
这个是不是我们想要的搜索结果???绝对不是,因为在我们看来,mother和mom有区别吗?同义词,都是妈妈的意思。like和liked有区别吗?没有,都是喜欢的意思,只不过一个是现在时,一个是过去时。little和small有区别吗?同义词,都是小小的。dog和dogs有区别吗?狗,只不过一个是单数,一个是复数。
normalization 作用:时态的转换,单复数的转换,同义词的转换,大小写的转换。
normalization,建立倒排索引的时候,会执行一个操作,也就是说对拆分出的各个单词进行相应的处理,以提升后面搜索的时候能够搜索到相关联的文档的概率
mom —> mother
liked —> like
small —> little
dogs —> dog
重新建立倒排索引,加入normalization,再次用mother liked little dog搜索,就可以搜索到了
word doc1 doc2
I * *
really *
like * * liked --> like
my * *
little * small --> little
dog * * dogs --> dog
and *
think *
mom * *
also *
them *
He *
never *
any *
so *
hope *
that *
will *
not *
expect *
me *
to *
him *
mother like little dog,先分词,再normalization
mother --> mom
like --> like
little --> little
dog --> dog
doc1和doc2都会搜索出来
doc1:I really liked my small dogs, and I think my mom also liked them.
doc2:He never liked any dogs, so I hope that my mom will not expect me to liked him.