blocks|key|1314066|text|在Ruby+Linguistics上有一些东西和一些链接，尽管它看起来还没有接近NLTK的Python.|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|1314067|entityMap|0|LINK|mutability|MUTABLE|url|http://www.ohloh.net/p/8375|1|http://www.ohloh.net/p/nltk^0|1|G|0|14|4|1|0^^$0|@$1|2|3|4|5|6|7|N|8|@]|9|@$A|O|B|P|1|Q]|$A|R|B|S|1|T]]|C|$]]|$1|D|3|-4|5|6|7|U|8|@]|9|@]|C|$]]]|E|$F|$5|G|H|I|C|$J|K]]|L|$5|G|H|I|C|$J|M]]]]

There are some things at <a href="http://www.ohloh.net/p/8375" rel="noreferrer">Ruby Linguistics</a> and some links therefrom, though it doesn't seem anywhere close to what <a href="http://www.ohloh.net/p/nltk" rel="noreferrer">NLTK</a> is for Python, yet.

blocks|key|1314148|text|您需要更具体地说明这些“一般特征”是什么。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|1314149|在NLP中，句子的“一般特征”可以表示一百万种不同的东西-情感分析(即说话者的态度)，基本的词性标记，人称代词的使用，句子包含主动动词还是被动动词，动词的时态和语态是什么……|1314150|我不介意你含糊其辞地描述它，但如果我们不知道你的要求是什么，我们就不太可能具体地帮助你。|1314151|我的一般建议，特别是对于NLP，是你应该得到最好的工具设计的工作，而不是限制自己只使用一种特定的语言。将自己限制为一种特定的语言对于那些通用工具随处可见的任务来说是很好的，但NLP不是其中之一。|1314152|与Twitter合作的另一个问题是，许多句子将是半生不熟的，或者以奇怪而奇妙的方式压缩--这是大多数NLP工具都没有训练过的。为了帮助做到这一点，NUS+SMS+Corpus由“大约10,000条学生收集的短信”组成。由于类似的限制和用法，分析可能会对您使用Twitter的探索有所帮助。|offset|length|1314153|如果你说得更具体一些，我会尝试列出一些有用的工具。|1314154|entityMap|0|LINK|mutability|MUTABLE|url|http://www.comp.nus.edu.sg/~rpnlpir/downloads/corpora/smsCorpus/^0|0|0|0|0|21|E|0|0|0^^$0|@$1|2|3|4|5|6|7|V|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|W|8|@]|9|@]|A|$]]|$1|D|3|E|5|6|7|X|8|@]|9|@]|A|$]]|$1|F|3|G|5|6|7|Y|8|@]|9|@]|A|$]]|$1|H|3|I|5|6|7|Z|8|@]|9|@$J|10|K|11|1|12]]|A|$]]|$1|L|3|M|5|6|7|13|8|@]|9|@]|A|$]]|$1|N|3|-4|5|6|7|14|8|@]|9|@]|A|$]]]|O|$P|$5|Q|R|S|A|$T|U]]]]

You need to be much more specific about what these "general characteristics" are.

In NLP "general characteristics" of a sentence can mean a million different things - sentiment analysis (ie, the attitude of the speaker), basic part of speech tagging, use of personal pronoun, does the sentence contain active or passive verbs, what's the tense and voice of the verbs...

I don't mind if you're vague about describing it, but if we don't know what you're asking it's highly unlikely we can be specific in helping you.

My general suggestion, especially for NLP, is you should get the tool best designed for the job instead of limiting yourself to a specific language. Limiting yourself to a specific language is fine for some tasks where the general tools are implemented everywhere, but NLP is not one of those.

The other issue in working with Twitter is a great deal of the sentences there will be half baked or compressed in strange and wonderful ways - which most NLP tools aren't trained for. To help there, the <a href="http://www.comp.nus.edu.sg/~rpnlpir/downloads/corpora/smsCorpus/" rel="nofollow noreferrer">NUS SMS Corpus</a> consists of "about 10,000 SMS messages collected by students". Due to the similar restrictions and usage, analysing that may be helpful in your explorations with Twitter.

If you're more specific I'll try and list some tools that will help.

blocks|key|1529359|text|您可以始终使用jruby和java库。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|1529360|编辑:能够在jvm上原生执行ruby，并且可以轻松地利用java库，这对ruby爱好者来说是一个很大的优势。这是一个很好的选择，应该在这种情况下考虑。|1529361|Which+NLP+toolkit+to+use+in+JAVA?|offset|length|1529362|entityMap|0|LINK|mutability|MUTABLE|url|https://stackoverflow.com/questions/895893/which-nlp-toolkit-to-use-in-java^0|0|0|0|X|0|0^^$0|@$1|2|3|4|5|6|7|P|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|Q|8|@]|9|@]|A|$]]|$1|D|3|E|5|6|7|R|8|@]|9|@$F|S|G|T|1|U]]|A|$]]|$1|H|3|-4|5|6|7|V|8|@]|9|@]|A|$]]]|I|$J|$5|K|L|M|A|$N|O]]]]

You can always use jruby and use the java libraries.

EDIT: The ability to do ruby natively on the jvm and easily leverage java libraries is a big plus for rubyists. This is a good option that should be considered in a situation like this.

<a href="https://stackoverflow.com/questions/895893/which-nlp-toolkit-to-use-in-java">Which NLP toolkit to use in JAVA?</a>

blocks|key|1529392|text|我找到了一篇很好的文章，详细介绍了Ruby+here中的一些自然语言处理算法。这包括词干分析器、日期时间分析器和语法分析器。|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|1529393|entityMap|0|LINK|mutability|MUTABLE|url|http://blog.nicksieger.com/articles/2006/10/22/rubyconf-natural-language-generation-and-processing-in-ruby^0|M|4|0|0^^$0|@$1|2|3|4|5|6|7|L|8|@]|9|@$A|M|B|N|1|O]]|C|$]]|$1|D|3|-4|5|6|7|P|8|@]|9|@]|C|$]]]|E|$F|$5|G|H|I|C|$J|K]]]]

I found an excellent article detailing some NLP algorithms in Ruby <a href="http://blog.nicksieger.com/articles/2006/10/22/rubyconf-natural-language-generation-and-processing-in-ruby" rel="noreferrer">here</a>. This includes stemmers, date time parsers and grammar parsers.

blocks|key|1529423|text|我会看看马克·沃森的免费书“Practical+Semantic+Web+and+Linked+Data+Applications,+Java,+Scala,+Clojure,+and+JRuby+Edition”。他有使用java、clojure、ruby和scala的NLP章节。他还提供了指向您所需资源的链接。|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|1529424|entityMap|0|LINK|mutability|MUTABLE|url|http://www.markwatson.com/opencontent/^0|E|2K|0|0^^$0|@$1|2|3|4|5|6|7|L|8|@]|9|@$A|M|B|N|1|O]]|C|$]]|$1|D|3|-4|5|6|7|P|8|@]|9|@]|C|$]]]|E|$F|$5|G|H|I|C|$J|K]]]]

I would check out Mark Watson's free book <a href="http://www.markwatson.com/opencontent/" rel="nofollow">Practical Semantic Web and Linked Data Applications, Java, Scala, Clojure, and JRuby Edition</a>. He has chapters on NLP using java, clojure, ruby, and scala. He also provides links to the resources you need.

blocks|key|1314302|text|TREAT+----是我所知道的最全面的REtrieval工具包：https://github.com/louismullie/treat/wiki/|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|1314303|entityMap|0|LINK|mutability|MUTABLE|url|https://github.com/louismullie/treat/wiki/^0|X|16|0|0^^$0|@$1|2|3|4|5|6|7|L|8|@]|9|@$A|M|B|N|1|O]]|C|$]]|$1|D|3|-4|5|6|7|P|8|@]|9|@]|C|$]]]|E|$F|$5|G|H|I|C|$J|K]]]]

TREAT – the Text REtrieval and Annotation Toolkit – is the most comprehensive toolkit I know of for Ruby: <a href="https://github.com/louismullie/treat/wiki/" rel="noreferrer">https://github.com/louismullie/treat/wiki/</a>

blocks|key|1529504|text|试试这个|type|unstyled|depth|inlineStyleRanges|entityRanges|data|1529505|https://github.com/louismullie/stanford-core-nlp|offset|length|1529506|关于stanford-core-nlp+gem|1529507|这个gem为Stanford+Core+NLP包提供了高级Ruby绑定，这是一组自然语言处理工具，用于标记化、句子分割、词性标记、词汇化以及英语、法语和德语的解析。该软件包还提供英文的命名实体识别和共指解析。|1529508|http://nlp.stanford.edu/software/corenlp.shtml演示页面http://nlp.stanford.edu:8080/corenlp/|1529509|entityMap|0|LINK|mutability|MUTABLE|url|1|http://nlp.stanford.edu/software/corenlp.shtml|2|http://nlp.stanford.edu:8080/corenlp/^0|0|0|1C|0|0|0|0|0|1A|1|1E|11|2|0^^$0|@$1|2|3|4|5|6|7|W|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|X|8|@]|9|@$D|Y|E|Z|1|10]]|A|$]]|$1|F|3|G|5|6|7|11|8|@]|9|@]|A|$]]|$1|H|3|I|5|6|7|12|8|@]|9|@]|A|$]]|$1|J|3|K|5|6|7|13|8|@]|9|@$D|14|E|15|1|16]|$D|17|E|18|1|19]]|A|$]]|$1|L|3|-4|5|6|7|1A|8|@]|9|@]|A|$]]]|M|$N|$5|O|P|Q|A|$R|C]]|S|$5|O|P|Q|A|$R|T]]|U|$5|O|P|Q|A|$R|V]]]]

Try this one 

<a href="https://github.com/louismullie/stanford-core-nlp" rel="nofollow">https://github.com/louismullie/stanford-core-nlp</a>

About stanford-core-nlp gem

This gem provides high-level Ruby bindings to the Stanford Core NLP package, a set natural language processing tools for tokenization, sentence segmentation, part-of-speech tagging, lemmatization, and parsing of English, French and German. The package also provides named entity recognition and coreference resolution for English.

<a href="http://nlp.stanford.edu/software/corenlp.shtml" rel="nofollow">http://nlp.stanford.edu/software/corenlp.shtml</a> 
demo page 
<a href="http://nlp.stanford.edu:8080/corenlp/" rel="nofollow">http://nlp.stanford.edu:8080/corenlp/</a>

blocks|key|1529556|text|对于希望实现更轻量级和更简单的东西的人来说，这个选项对我来说效果很好。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|1529557|https://github.com/yohasebe/engtagger|offset|length|1529558|entityMap|0|LINK|mutability|MUTABLE|url^0|0|0|11|0|0^^$0|@$1|2|3|4|5|6|7|M|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|N|8|@]|9|@$D|O|E|P|1|Q]]|A|$]]|$1|F|3|-4|5|6|7|R|8|@]|9|@]|A|$]]]|G|$H|$5|I|J|K|A|$L|C]]]]

For people looking for something more lightweight and simple to implement this option worked well for me.

<a href="https://github.com/yohasebe/engtagger" rel="nofollow">https://github.com/yohasebe/engtagger</a>

blocks|key|1529587|text|我在GitHub上维护了一个Ruby+Natural+Language+Processing+resources+(库、API和演示文稿)列表，其中涵盖了此处列出的其他答案中列出的库以及一些其他库。|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|1529588|entityMap|0|LINK|mutability|MUTABLE|url|https://github.com/diasks2/ruby-nlp^0|E|16|0|0^^$0|@$1|2|3|4|5|6|7|L|8|@]|9|@$A|M|B|N|1|O]]|C|$]]|$1|D|3|-4|5|6|7|P|8|@]|9|@]|C|$]]]|E|$F|$5|G|H|I|C|$J|K]]]]

I maintain a list of <a href="https://github.com/diasks2/ruby-nlp" rel="noreferrer">Ruby Natural Language Processing resources</a> (libraries, APIs, and presentations) on GitHub that covers the libraries listed in the other answers here as well as some additional libraries.

I'm looking to do some sentence analysis (mostly for twitter apps) and infer some general characteristics. Are there any good natural language processing libraries for this sort of thing in Ruby?

Similar to <a href="https://stackoverflow.com/questions/870460/java-is-there-a-good-natural-language-processing-library">Is there a good natural language processing library</a> but for Ruby. I'd prefer something very general, but any leads are appreciated!

Natural Language Processing in Ruby

自然语言处理

短信

Python

GitHub

我希望做一些句子分析(主要是为twitter应用程序)，并推断一些一般特征。在Ruby中有没有很好的自然语言处理库来处理这类事情？类似于，但用于Ruby。我更喜欢一些非常一般的东西，但任何线索都是感激的！

问Ruby中的自然语言处理
EN

社区

活动

资源

关于

腾讯云开发者

热门产品

热门推荐

更多推荐

问Ruby中的自然语言处理EN

社区

活动

资源

关于

腾讯云开发者

热门产品

热门推荐

更多推荐

问Ruby中的自然语言处理
EN