字符串算法书籍
关于字符串算法的帖子有很多：
- 查找具有相似文本的文章的算法、
- < a href="https://stackoverflow.com/questions/451884/similar-string-algorithm">类似字符串算法，
- 高效的字符串匹配算法
但是一般文献中没有提及。
有人可以推荐一本可以彻底探索各种字符串算法的书吗？ 特别感兴趣的主题是近似字符串匹配[诸如谷歌提供的校正搜索字符串变体之类的东西:)]。
非常感谢您的建议。
There have been numerous posts on string algorithms:
- Algorithm to find articles with similar text,
- Similar String algorithm,
- Efficient string matching algorithm
However, no general literature was mentioned.
Could anyone recommend a book(s) that would thoroughly explore various string algorithms?
The topic which is of special interest is approximate string matching [things like google-offered corrected search string variants :) ].
Thanks a lot for advice.
如果你对这篇内容有疑问，欢迎到本站社区发帖提问 参与讨论，获取更多帮助，或者扫码二维码加入 Web 技术交流群。
绑定邮箱获取回复消息
由于您还没有绑定你的真实邮箱，如果其他用户或者作者回复了您的评论，将不能在第一时间通知您！
发布评论
评论（5）
我很惊讶没有人提到 Dan Gusfield 的优秀著作字符串、树和序列的算法< /a> 其中涵盖了比任何人可能需要的更详细的字符串算法。它对我几年前从事的蛋白质测序项目非常有用。读完本书后，您将学到：
I'm surprised no-one has mentioned Dan Gusfield's excellent book Algorithms on Strings, Trees and Sequences which covers string algorithms in more detail than anyone would probably need. It served me very well for a project on protein sequencing that I was working on a few years ago. After reading this book you will learn:
这不是书籍推荐，但这个库和网站是一个提供大量高效字符串匹配算法实现的库：
http://www.dcs.shef.ac.uk/~sam/simmetrics.html
它还提供了进一步学习每个内容以及每个内容最适用的链接。
This is not a book recommendation, but this library and site is a library that offers plenty of efficient string matching algorithm implementations:
http://www.dcs.shef.ac.uk/~sam/simmetrics.html
It also provides links to further learning for each and where each is best applicable.
弦乐学瑰宝
Jewels of Stringology
CLR 有一些字符串处理算法，但并不是特定于它们的。
包括：
CLR has some string processing algorithms, but it's not specific to them.
Including:
TRE 是一个实现近似匹配的开源库。 关于页面有一些关于它如何工作的有趣提示，尽管我不确定它是否提供了您正在寻找的某种深入分析。从这个角度来看，源代码可能更具启发性。
TRE is an open-source library that implements approximate matching. The About page has some interesting hints about how it works, although I'm not sure it provides the sort of in-depth analysis you're looking for. The source code is probably more enlightening from that perspective.