SOLR和自然语言解析-我可以使用它吗? [英] SOLR and Natural Language Parsing - Can I use it?
问题描述
尽管该问题的答案非常好，但我想知道我是否可以利用我花所有的时间了解NLP的SOLR.
While the answer for that question is excellent, I was wondering if I could make use of all the time I spent getting to know SOLR for my NLP.
我之所以想到SOLR，是因为:
I thought of SOLR because:
- 它有很多标记器，并且执行很多NLP.
- 开箱即用非常有用.
- 这是一个宁静的分布式应用程序，因此很容易挂接
- 我已经花了一些时间，所以使用它可以节省我的时间.
我可以使用Solr吗?
尽管以上原因很好，但我不太了解SOLR，所以我需要知道它是否适合我的要求.
Can I use Solr?
Although the above reasons are good, I don't know SOLR THAT well, so I need to know if it would be appropriate for my requirements.
理想情况下，我想配置SOLR，然后能够向SOLR发送一些文本，并检索已编入索引的内容.
Ideally, I'd like to configure SOLR, and then be able to send SOLR some text, and retrieve the indexed tonkenized content.
我正在研究较大推荐引擎中的一小部分.
I'm working on a small component of a bigger recommendation engine.
推荐答案
我想您可以使用Solr并将其与其他工具结合使用.标记化，停用词删除，词干，甚至同义词都随Solr开箱即用.如果您需要命名实体识别或基本名词短语提取，则需要使用 OpenNLP 或同等工具作为预处理阶段.您可能需要出于检索目的的术语向量.
I guess you can use Solr and combine it with other tools. Tokenization, stop word removal, stemming, and even synonyms come out of the box with Solr. If you need named entity recognition or base noun-phrase extraction, you need to use OpenNLP or an equivalent tool as a pre-processing stage. You will probably need term vectors for your retrieval purposes. Integrating Apache Mahout with Apache Lucene and Solr may be useful as it discusses Lucene and Solr integration with a machine learning (including recommendation) engine. Other then that, feel free to ask further more specific questions.
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