快速入門:使用 Node.js 來呼叫文字分析認知服務Quickstart: Using Node.js to call the Text Analytics Cognitive Service

本文示範如何使用 文字分析 API  與 Node.JS 來偵測語言分析情感擷取關鍵片語,以及識別已連結實體This article shows you how to detect language, analyze sentiment, extract key phrases, and identify linked entities using the Text Analytics APIs with Node.JS.

如需 API 的技術文件,請參閱 API 定義Refer to the API definitions for technical documentation for the APIs.

必要條件Prerequisites

您必須有具備文字分析 API 存取權的認知服務 API 訂用帳戶You must have a Cognitive Services API subscription with access to the Text Analytics API. 如果您沒有訂用帳戶,可以建立免費帳戶If you don't have a subscription, you can create an account for free. 在繼續之前,您必須有啟用帳戶之後所提供的文字分析訂用帳戶金鑰。Before continuing, you will need the Text Analytics subscription key provided after activating your account.

您也必須具備註冊時產生的端點和存取金鑰You must also have the endpoint and access key that was generated for you during sign-up.

偵測語言種類Detect language

語言偵測 API 會使用偵測語言方法 (英文) 來偵測文字文件的語言。The Language Detection API detects the language of a text document, using the Detect Language method.

  1. 在您最愛的 IDE (或您桌面上的資料夾) 中建立新的 Node.JS 專案。Create a new Node.JS project in your favorite IDE or a folder on your desktop.
  2. 將下方提供的程式碼新增至新的 .js 檔案。Add the code provided below to a new .js file.
  3. 在 Azure 中,以文字分析資源中的訂用帳戶金鑰取代 accessKey 值。Replace the accessKey value with a subscription key from your Text Analytics resource in Azure.
  4. uri 中的位置 (目前為 westus) 取代為您註冊的區域。Replace the location in uri (currently westus) to the region you signed up for.
  5. 從您的 IDE 或命令列來執行程式,例如 npm startnode detect.jsRun the program from your IDE or command line, for example npm start or node detect.js.
'use strict';

let https = require ('https');

// **********************************************
// *** Update or verify the following values. ***
// **********************************************

// Replace the accessKey string value with your valid access key.
let accessKey = 'enter key here';

// Replace or verify the region.

// You must use the same region in your REST API call as you used to obtain your access keys.
// For example, if you obtained your access keys from the westus region, replace 
// "westcentralus" in the URI below with "westus".

// NOTE: Free trial access keys are generated in the westcentralus region, so if you are using
// a free trial access key, you should not need to change this region.
let uri = 'westus.api.cognitive.microsoft.com';
let path = '/text/analytics/v2.1/languages';

let response_handler = function (response) {
    let body = '';
    response.on ('data', function (d) {
        body += d;
    });
    response.on ('end', function () {
        let body_ = JSON.parse (body);
        let body__ = JSON.stringify (body_, null, '  ');
        console.log (body__);
    });
    response.on ('error', function (e) {
        console.log ('Error: ' + e.message);
    });
};

let get_language = function (documents) {
    let body = JSON.stringify (documents);

    let request_params = {
        method : 'POST',
        hostname : uri,
        path : path,
        headers : {
            'Ocp-Apim-Subscription-Key' : accessKey,
        }
    };

    let req = https.request (request_params, response_handler);
    req.write (body);
    req.end ();
}

let documents = { 'documents': [
    { 'id': '1', 'text': 'This is a document written in English.' },
    { 'id': '2', 'text': 'Este es un document escrito en Español.' },
    { 'id': '3', 'text': '这是一个用中文写的文件' }
]};

get_language (documents);

語言偵測回應Language detection response

如以下範例所示,成功的回應會以 JSON 格式來傳回:A successful response is returned in JSON, as shown in the following example:


{
   "documents": [
      {
         "id": "1",
         "detectedLanguages": [
            {
               "name": "English",
               "iso6391Name": "en",
               "score": 1.0
            }
         ]
      },
      {
         "id": "2",
         "detectedLanguages": [
            {
               "name": "Spanish",
               "iso6391Name": "es",
               "score": 1.0
            }
         ]
      },
      {
         "id": "3",
         "detectedLanguages": [
            {
               "name": "Chinese_Simplified",
               "iso6391Name": "zh_chs",
               "score": 1.0
            }
         ]
      }
   ],
   "errors": [

   ]
}


分析人氣Analyze sentiment

情感分析 API 會使用 Sentiment 方法,偵測一組文字記錄中的情緒態度。The Sentiment Analysis API detects the sentiment of a set of text records, using the Sentiment method. 藉由分析原始文字而獲得有關於正面或負面情感的線索,情感分析可用來了解客戶對您的品牌或主題有何看法。Sentiment analysis can be used to find out what customers think of your brand or topic by analyzing raw text for clues about positive or negative sentiment. 下列範例會為兩份文件提供評分,一份是英文,另一份則是西班牙文。The following example provides scores for two documents, one in English and another in Spanish.

  1. 在您最愛的 IDE (或您桌面上的資料夾) 中建立新的 Node.JS 專案。Create a new Node.JS project in your favorite IDE or a folder on your desktop.
  2. 將下方提供的程式碼新增至新的 .js 檔案。Add the code provided below to a new .js file.
  3. 在 Azure 中,以文字分析資源中的訂用帳戶金鑰取代 accessKey 值。Replace the accessKey value with a subscription key from your Text Analytics resource in Azure.
  4. uri 中的位置 (目前為 westus) 取代為您註冊的區域。Replace the location in uri (currently westus) to the region you signed up for.
  5. 從您的 IDE 或命令列來執行程式,例如 npm startnode sentiment.jsRun the program from your IDE or command line, for example npm start or node sentiment.js.
'use strict';

let https = require ('https');

// **********************************************
// *** Update or verify the following values. ***
// **********************************************

// Replace the accessKey string value with your valid access key.
let accessKey = 'enter key here';

// Replace or verify the region.

// You must use the same region in your REST API call as you used to obtain your access keys.
// For example, if you obtained your access keys from the westus region, replace 
// "westcentralus" in the URI below with "westus".

// NOTE: Free trial access keys are generated in the westcentralus region, so if you are using
// a free trial access key, you should not need to change this region.
let uri = 'westus.api.cognitive.microsoft.com';
let path = '/text/analytics/v2.1/sentiment';

let response_handler = function (response) {
    let body = '';
    response.on ('data', function (d) {
        body += d;
    });
    response.on ('end', function () {
        let body_ = JSON.parse (body);
        let body__ = JSON.stringify (body_, null, '  ');
        console.log (body__);
    });
    response.on ('error', function (e) {
        console.log ('Error: ' + e.message);
    });
};

let get_sentiments = function (documents) {
    let body = JSON.stringify (documents);

    let request_params = {
        method : 'POST',
        hostname : uri,
        path : path,
        headers : {
            'Ocp-Apim-Subscription-Key' : accessKey,
        }
    };

    let req = https.request (request_params, response_handler);
    req.write (body);
    req.end ();
}

let documents = { 'documents': [
    { 'id': '1', 'language': 'en', 'text': 'I really enjoy the new XBox One S. It has a clean look, it has 4K/HDR resolution and it is affordable.' },
    { 'id': '2', 'language': 'es', 'text': 'Este ha sido un dia terrible, llegué tarde al trabajo debido a un accidente automobilistico.' },
]};

get_sentiments (documents);

情感分析回應Sentiment analysis response

如果評分較接近 1.0,表示結果為正面,如果評分較接近 0.0,則表示為負面。The result is measured as positive if it's scored closer to 1.0 and negative if it's scored closer to 0.0. 如以下範例所示,成功的回應會以 JSON 格式來傳回:A successful response is returned in JSON, as shown in the following example:

{
   "documents": [
      {
         "score": 0.99984133243560791,
         "id": "1"
      },
      {
         "score": 0.024017512798309326,
         "id": "2"
      },
   ],
   "errors": [   ]
}

擷取關鍵片語Extract key phrases

關鍵片語擷取 API 會使用關鍵片語方法從文字文件擷取關鍵片語。The Key Phrase Extraction API extracts key-phrases from a text document, using the Key Phrases method. 關鍵片語擷取可用來快速識別文件或文字的重點。Key phrase extraction is used to quickly identify the main points of a document or text. 以下範例會擷取英文和西班牙文文件的關鍵片語。The following example extracts key phrases for both English and Spanish documents.

  1. 在您最愛的 IDE (或您桌面上的資料夾) 中建立新的 Node.JS 專案。Create a new Node.JS project in your favorite IDE or a folder on your desktop.
  2. 將下方提供的程式碼新增至新的 .js 檔案。Add the code provided below to a new .js file.
  3. 在 Azure 中,以文字分析資源中的訂用帳戶金鑰取代 accessKey 值。Replace the accessKey value with a subscription key from your Text Analytics resource in Azure.
  4. uri 中的位置 (目前為 westus) 取代為您註冊的區域。Replace the location in uri (currently westus) to the region you signed up for.
  5. 從您的 IDE 或命令列來執行程式,例如 npm startnode key-phrases.jsRun the program from your IDE or command line, for example npm start or node key-phrases.js.
'use strict';

let https = require ('https');

// **********************************************
// *** Update or verify the following values. ***
// **********************************************

// Replace the accessKey string value with your valid access key.
let accessKey = 'enter key here';

// Replace or verify the region.

// You must use the same region in your REST API call as you used to obtain your access keys.
// For example, if you obtained your access keys from the westus region, replace 
// "westcentralus" in the URI below with "westus".

// NOTE: Free trial access keys are generated in the westcentralus region, so if you are using
// a free trial access key, you should not need to change this region.
let uri = 'westus.api.cognitive.microsoft.com';
let path = '/text/analytics/v2.1/keyPhrases';

let response_handler = function (response) {
    let body = '';
    response.on ('data', function (d) {
        body += d;
    });
    response.on ('end', function () {
        let body_ = JSON.parse (body);
        let body__ = JSON.stringify (body_, null, '  ');
        console.log (body__);
    });
    response.on ('error', function (e) {
        console.log ('Error: ' + e.message);
    });
};

let get_key_phrases = function (documents) {
    let body = JSON.stringify (documents);

    let request_params = {
        method : 'POST',
        hostname : uri,
        path : path,
        headers : {
            'Ocp-Apim-Subscription-Key' : accessKey,
        }
    };

    let req = https.request (request_params, response_handler);
    req.write (body);
    req.end ();
}

let documents = { 'documents': [
    { 'id': '1', 'language': 'en', 'text': 'I really enjoy the new XBox One S. It has a clean look, it has 4K/HDR resolution and it is affordable.' },
    { 'id': '2', 'language': 'es', 'text': 'Si usted quiere comunicarse con Carlos, usted debe de llamarlo a su telefono movil. Carlos es muy responsable, pero necesita recibir una notificacion si hay algun problema.' },
    { 'id': '3', 'language': 'en', 'text': 'The Grand Hotel is a new hotel in the center of Seattle. It earned 5 stars in my review, and has the classiest decor I\'ve ever seen.' }
]};

get_key_phrases (documents);

關鍵片語擷取回應Key phrase extraction response

會以 JSON 傳回成功的回應,如下列範例所示:A successful response is returned in JSON, as shown in the following example:

{
   "documents": [
      {
         "keyPhrases": [
            "HDR resolution",
            "new XBox",
            "clean look"
         ],
         "id": "1"
      },
      {
         "keyPhrases": [
            "Carlos",
            "notificacion",
            "algun problema",
            "telefono movil"
         ],
         "id": "2"
      },
      {
         "keyPhrases": [
            "new hotel",
            "Grand Hotel",
            "review",
            "center of Seattle",
            "classiest decor",
            "stars"
         ],
         "id": "3"
      }
   ],
   "errors": [  ]
}

識別已連結實體Identify linked entities

實體 API 會使用實體方法來識別文字文件中的已知實體。The Entities API identifies well-known entities in a text document, using the Entities method. 實體可從像是「北美洲」的文字擷取字組,再提供此字組的類型和/或維基百科連結給您。Entities extract words from text, like "United States", then give you the type and/or Wikipedia link for this word(s). 「北美洲」的類型為 location,而維基百科的連結為 https://en.wikipedia.org/wiki/United_StatesThe type for "United States" is location, while the link to Wikipedia is https://en.wikipedia.org/wiki/United_States. 以下範例會識別英文文件的實體。The following example identifies entities for English documents.

  1. 在您最愛的 IDE (或您桌面上的資料夾) 中建立新的 Node.JS 專案。Create a new Node.JS project in your favorite IDE or a folder on your desktop.
  2. 將下方提供的程式碼新增至新的 .js 檔案。Add the code provided below to a new .js file.
  3. 在 Azure 中,以文字分析資源中的訂用帳戶金鑰取代 accessKey 值。Replace the accessKey value with a subscription key from your Text Analytics resource in Azure.
  4. uri 中的位置 (目前為 westus) 取代為您註冊的區域。Replace the location in uri (currently westus) to the region you signed up for.
  5. 從您的 IDE 或命令列來執行程式,例如 npm startnode entities.jsRun the program from your IDE or command line, for example npm start or node entities.js.
'use strict';

let https = require ('https');

// **********************************************
// *** Update or verify the following values. ***
// **********************************************

// Replace the accessKey string value with your valid access key.
let accessKey = 'enter key here';

// Replace or verify the region.

// You must use the same region in your REST API call as you used to obtain your access keys.
// For example, if you obtained your access keys from the westus region, replace 
// "westcentralus" in the URI below with "westus".

// NOTE: Free trial access keys are generated in the westcentralus region, so if you are using
// a free trial access key, you should not need to change this region.
let uri = 'westus.api.cognitive.microsoft.com';
let path = '/text/analytics/v2.1/entities';

let response_handler = function (response) {
    let body = '';
    response.on ('data', function (d) {
        body += d;
    });
    response.on ('end', function () {
        let body_ = JSON.parse (body);
        let body__ = JSON.stringify (body_, null, '  ');
        console.log (body__);
    });
    response.on ('error', function (e) {
        console.log ('Error: ' + e.message);
    });
};

let get_entities = function (documents) {
    let body = JSON.stringify (documents);

    let request_params = {
        method : 'POST',
        hostname : uri,
        path : path,
        headers : {
            'Ocp-Apim-Subscription-Key' : accessKey,
        }
    };

    let req = https.request (request_params, response_handler);
    req.write (body);
    req.end ();
}

let documents = { 'documents': [
    { 'id': '1', 'language': 'en', 'text': 'Microsoft is an It company.' }
]};

get_entities (documents);

實體擷取回應Entity extraction response

如以下範例所示,成功的回應會以 JSON 格式來傳回:A successful response is returned in JSON, as shown in the following example:

{  
   "documents":[  
      {  
         "id":"1",
         "entities":[  
            {  
               "name":"Microsoft",
               "matches":[  
                  {  
                     "wikipediaScore":0.20872054383103444,
                     "entityTypeScore":0.99996185302734375,
                     "text":"Microsoft",
                     "offset":0,
                     "length":9
                  }
               ],
               "wikipediaLanguage":"en",
               "wikipediaId":"Microsoft",
               "wikipediaUrl":"https://en.wikipedia.org/wiki/Microsoft",
               "bingId":"a093e9b9-90f5-a3d5-c4b8-5855e1b01f85",
               "type":"Organization"
            },
            {  
               "name":"Technology company",
               "matches":[  
                  {  
                     "wikipediaScore":0.82123868042800585,
                     "text":"It company",
                     "offset":16,
                     "length":10
                  }
               ],
               "wikipediaLanguage":"en",
               "wikipediaId":"Technology company",
               "wikipediaUrl":"https://en.wikipedia.org/wiki/Technology_company",
               "bingId":"bc30426e-22ae-7a35-f24b-454722a47d8f"
            }
         ]
      }
   ],
    "errors":[]
}

後續步驟Next steps

另請參閱See also

文字分析概觀Text Analytics overview
常見問題集 (FAQ)Frequently asked questions (FAQ)