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The best practice of connecting Baidu AI interface to implement sentiment analysis in Java language

Aug 26, 2023 am 09:43 AM
java emotion analysis Baidu ai

The best practice of connecting Baidu AI interface to implement sentiment analysis in Java language

The best practice of docking Baidu AI interface to implement sentiment analysis in Java language

Introduction:
Sentiment analysis is an important application in the field of natural language processing. It can be used to analyze the emotional tendencies contained in texts, helping companies understand users' emotional attitudes and make more appropriate decisions. Baidu AI platform provides a rich set of natural language processing APIs, including sentiment analysis APIs. This article will introduce how to use Java language to connect to Baidu AI sentiment analysis interface and implement the best practices of sentiment analysis.

  1. Create Baidu AI Application
    First, we need to create an application on the Baidu AI platform to obtain the API Key and Secret Key. Open the official website of Baidu AI Open Platform (https://ai.baidu.com/) in your browser, click Login/Register in the upper right corner to complete the login or registration process. Then, click the console to enter the application management page, click "Create Application", fill in the application name and select the language as Java, and then submit the creation. After successful creation, you can see your API Key and Secret Key on the application management page.
  2. Introducing dependencies
    In the Java project, we need to introduce the Java SDK to call the Baidu AI sentiment analysis API. In the project's pom.xml file, add the following dependencies:
<dependency>
    <groupId>com.baidu.aip</groupId>
    <artifactId>java-sdk</artifactId>
    <version>4.7.0</version>
</dependency>
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  1. Implementing sentiment analysis
    In the Java code, we need to import the corresponding classes and methods to implement sentiment analysis . The following is a sample code using Baidu AI sentiment analysis API:
import com.baidu.aip.nlp.AipNlp;
import org.json.JSONObject;

public class SentimentAnalysis {
    // 设置APPID/AK/SK
    public static final String APP_ID = "your_app_id";
    public static final String API_KEY = "your_api_key";
    public static final String SECRET_KEY = "your_secret_key";

    public static void main(String[] args) {
        // 初始化一个AipNlp
        AipNlp client = new AipNlp(APP_ID, API_KEY, SECRET_KEY);

        // 调用情感分析接口
        String text = "我今天感觉非常开心";
        JSONObject res = client.sentimentClassify(text, null);

        // 解析返回的结果
        int sentiment = res.getJSONArray("items").getJSONObject(0).getInt("sentiment");
        System.out.println("情感倾向:" + sentiment);
    }
}
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In the above example, we first initialize an AipNlp client and then call the sentiment analysis interface sentimentClassify , and pass in the text to be analyzed as a parameter. Finally, we parse the returned results to obtain emotional tendencies.

  1. Run the program
    Before running the program, we need to replace APP_ID, API_KEY and SECRET_KEY with the actual values ​​you obtained when creating the application on the Baidu AI platform.

Run the program in your Java IDE and you will see the output, which represents the emotional tendency of the text. You can analyze the user's emotional attitude based on the returned results and make corresponding decisions.

Conclusion:
By using Java language to connect to Baidu AI interface to implement sentiment analysis, we can easily analyze the emotional tendency in the text. Baidu AI platform provides simple and easy-to-use APIs, making sentiment analysis more convenient. In practical applications, you can adjust product strategies based on users' emotional attitudes, improve user experience, and further enhance business value.

Reference link:

  • Baidu AI Open Platform: https://ai.baidu.com/
  • Baidu AI Natural Language Processing API Document: https:/ /cloud.baidu.com/doc/NLP/index.html

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