如何在python中将一个列表中最"相似"的字符串映射到另一个列表？

Question

给出两个包含字符串的列表.

1. 一个包含世界各地的组织(主要是大学)的名称 - 不仅用英语写,而且总是使用拉丁字母.

2. 另一个列表主要包含完整地址,其中可能出现第一个列表中的字符串(组织).

一个例子:

addresses = [
             "Department of Computer Science, Katholieke Universiteit Leuven, Leuven, Belgium",
             "Machine Learning and Computational Biology Research Group, Max Planck Institutes     Tübingen, Tübingen, Germany 72076",
             "Department of Computer Science and Engineering, University of Washington, Seattle, USA 98185",
             "Knowledge Discovery Department, Fraunhofer IAIS, Sankt Augustin, Germany 53754",    
             "Computer Science Department, University of California, Santa Barbara, USA 93106",
             "Fraunhofer IAIS, Sankt Augustin, Germany",
             "Department of Computer Science, Cornell University, Ithaca, NY",
             "University of Wisconsin-Madison"
            ]

organisations = [
                 "Catholic University of Leuven"
                 "Fraunhofer IAIS"
                 "Cornell University of Ithaca"
                 "Tübingener Max Plank Institut"
                ]

如您所见,所需的映射将是:

"Department of Computer Science, Katholieke Universiteit Leuven, Leuven, Belgium",
--> Catholic University of  Leuven
"Machine Learning and Computational Biology Research Group, Max Planck Institutes     Tübingen, Tübingen, Germany 72076",
--> Max Plank Institut Tübingen
"Department of Computer Science and Engineering, University of Washington, Seattle, USA 98185",
--> --
"Knowledge Discovery Department, Fraunhofer IAIS, Sankt Augustin, Germany 53754",
--> Fraunhofer IAIS 
"Computer Science Department, University of California, Santa Barbara, USA 93106",
"Fraunhofer IAIS, Sankt Augustin, Germany",
--> Fraunhofer IAIS
"Department of Computer Science, Cornell University, Ithaca, NY"
--> "Cornell University of Ithaca",
"University of Wisconsin-Madison",
--> --

我的想法是使用某种"disctance-算法"来计算字符串的相似性.因为我不能仅仅通过这样做来寻找地址中的组织,if address in organisation因为它可能在不同的地方略有不同.所以我的第一个猜测是使用difflib模块.特别是difflib.get_close_matches()为每个地址选择组织列表中最接近的字符串的功能.但我不太自信,结果将足够准确.虽然我不知道我应该设置多高的接缝比例作为相似性度量.

在花费太多时间尝试difflib模块之前,我想在这里询问更有经验的人,如果这是正确的方法,或者是否有更合适的工具/方法来解决我的问题.谢谢!

PS:我不需要最佳解决方案.

Answer 1

您可以使用 soundex 或 metaphone 将句子翻译成音素列表，然后比较最相似的列表。

这是双变音位算法的 Python 实现。