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Keyword Extraction

フリーミアム
開発者 textanalysis
更新日 1ヶ月前
ツール
7/10
人気度
249ms
レイテンシ
97%
正常稼働率

「Keyword Extraction 」のドキュメント

キーワード抽出APIは、高度な自然言語処理および機械学習技術に基づいた、専門的なキーワード抽出サービスを提供します。ユーザーが提供したURLまたはドキュメントから重要な上位キーワードを抽出するために使用できます。私たちの自動キーワード抽出サービスをテストしたい場合は、私たちの無料の自動キーワード抽出オンラインデモを使用することができます:http://keywordextraction.net/keyword-extractor

全文を表示する
POSTKeyword Extraction for Text
POSTKeyword Extraction for URL
POSTKeyword Extraction for Text

テキストからのキーワード抽出

ヘッダーパラメータ
X-RapidAPI-HostSTRING
REQUIRED
X-RapidAPI-KeySTRING
REQUIRED
パラメータ(Option)
textSTRING
OPTIONALText to be extracted by Keyword Extractor
wordnumNUMBER
OPTIONALKeyword numbers to be extracted specified by user
コードスニペット
unirest.post("https://textanalysis-keyword-extraction-v1.p.rapidapi.com/keyword-extractor-text")
.header("X-RapidAPI-Host", "textanalysis-keyword-extraction-v1.p.rapidapi.com")
.header("X-RapidAPI-Key", "ログインしてキーを取得")
.header("Content-Type", "application/x-www-form-urlencoded")
.send("text=Keyword extraction is tasked with the automatic identification of terms that best describe the subject of a document. Key phrases, key terms, key segments or just keywords are the terminology which is used for defining the terms that represent the most relevant information contained in the document. Although the terminology is different, function is the same: characterization of the topic discussed in a document. Keyword extraction task is important problem in Text Mining, Information Retrieval and Natural Language Processing. Keyword assignment vs. extraction Keyword assignment methods can be roughly divided into: keyword assignment (keywords are chosen from controlled vocabulary or taxonomy) and keyword extraction (keywords are chosen from words that are explicitly mentioned in original text). Methods for automatic keyword extraction can be: supervised, semi-supervised and unsupervised. Unsupervised methods can be further divided into: simple statistics, linguistics, graph-based and other methods.")
.send("wordnum=5")
.end(function (result) {
  console.log(result.status, result.headers, result.body);
});
サンプルレスポンス
概要
リクエストURL: https://textanalysis-keyword-extraction-v1.p.rapidapi.com/keyword-extractor-text
リクエストメソッド: POST
レスポンスヘッダ
レスポンスボディ

SDKをインストール(NodeJS)

インストール

Node.jsでUnirestを使用するには、NPMモジュールをインストールしてください。

$ npm install unirest

インストール完了後は、簡単にリクエストを行うことができるようになります。

var unirest = require('unirest');

リクエスト

unirest.post("https://textanalysis-keyword-extraction-v1.p.rapidapi.com/keyword-extractor-text")
.header("X-RapidAPI-Host", "textanalysis-keyword-extraction-v1.p.rapidapi.com")
.header("X-RapidAPI-Key", "ログインしてキーを取得")
.header("Content-Type", "application/x-www-form-urlencoded")
.send("text=Keyword extraction is tasked with the automatic identification of terms that best describe the subject of a document. Key phrases, key terms, key segments or just keywords are the terminology which is used for defining the terms that represent the most relevant information contained in the document. Although the terminology is different, function is the same: characterization of the topic discussed in a document. Keyword extraction task is important problem in Text Mining, Information Retrieval and Natural Language Processing. Keyword assignment vs. extraction Keyword assignment methods can be roughly divided into: keyword assignment (keywords are chosen from controlled vocabulary or taxonomy) and keyword extraction (keywords are chosen from words that are explicitly mentioned in original text). Methods for automatic keyword extraction can be: supervised, semi-supervised and unsupervised. Unsupervised methods can be further divided into: simple statistics, linguistics, graph-based and other methods.")
.send("wordnum=5")
.end(function (result) {
  console.log(result.status, result.headers, result.body);
});
OAuth2認証
クライアントID
クライアントシークレット
OAuth2認証