# 自然語言處理

* 目前的文本挖掘都必須是由 NLP 技術來強化。舉例：<http://textminingonline.com/>

![tm.online](/files/-LnAgWZ03Avu9B9hv-va)

* NLP 的成熟與語言知識介入多深，決定了文本挖掘有趣到什麼程度。
* 商用的系統也出現不少。

## 自然語言處理技術重點

* 句法剖析 (Syntactic Parsing)/句塊抽取 (Chunking)
* 詞義排歧 (Word Sense Disambiguation, WSD)
* 共指消歧 (Co-reference Resolution)
* 命名實體辨識 (Named Entity Recognition, NER)

NLP 通常結合了各項**語言資源** (language resources)，如語料庫、詞彙知識庫 (lexical knowledge base)、知識本體 (ontologies) 等等來提升機器對於文本訊息的理解。

## 中文語言處理平台

* 卓騰語言科技[ Articut](https://api.droidtown.co)
* [語言雲](http://www.ltp-cloud.com)
* [玻森](http://bosonnlp.com/)

也可以利用 `Gate`平台，整合標記與自然語言處理模組來做。

## R 自然語言處理套件

<https://cran.r-project.org/web/views/NaturalLanguageProcessing.html>

* `openNLP`：Apache OpenNLP Tools Interface.
* `NLP`: Basic functions for Natural Language Processing.
* `coreNLP`：史丹佛大學自然語言處理工具集
* `KoNLP` 韓語自然語言處理
* `tmcn` 適應中文的 `tm` 改良，方便編碼轉換。
* `jiebaR`，`Rwordseg`中文斷詞

`openNLP` 和 `coreNLP` 是目前比較厲害的成果。以下用 [`coreNLP`](http://cran.r-project.org/web/packages/coreNLP) 為例

<http://github.com/statsmaths/coreNLP>

```
devtools::install_github("statsmaths/coreNLP")
download.file("http://nlp.stanford.edu/software/stanford-corenlp-full-2015-01-29.zip")
unzip("stanford-corenlp-full-2015-01-29.zip")
```

```
library(coreNLP)
initCoreNLP("stanford-corenlp-full-2015-01-29")
catInHat = c("the sun did not shine.", "it was too wet to play.","so we sat in the house all that cold, cold, wet day.")
output = annotateString(catInHat)
getToken(output)
getDependency(output)
getSentiment(output)
```


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://lab-of-ontologies-language-proce.gitbook.io/ladsbook/partiji-chu-zhi-shi/nlp.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.