Product review parsing service - Automotive

This topic describes how to use the product review parsing service for the automotive field. If the currently supported domains and industries do not meet your needs, you can join the NLP Self-Learning Platform Q&A Group 2 on DingTalk (Group ID: 44619071) for further assistance.

Activate the service and purchase a resource plan

Before you start, confirm that the service is activated. After the service is activated, you can purchase a resource plan.

• Activate service: Activation page

• Purchase resource plan: Purchase page

Service invocation and debugging

For information about how to call the model, see Model invocation.

For software development kit (SDK) examples, see SDK examples.

Debug

Configure access credentials (AKSK) using environment variables

1. Notes:

   1. An AccessKey for an Alibaba Cloud account has full access permissions to all APIs. This poses a high security threat. We strongly recommend that you create and use a Resource Access Management (RAM) user to make API calls or perform routine operations and maintenance (O&M). To create a RAM user, log on to the RAM console.

   2. To prevent security threats from key leaks, do not hard-code your AccessKey ID and AccessKey secret in your code. Instead, configure them as environment variables.

2. Configuration on Linux and macOS

   export NLP_AK_ENV=<access_key_id>
   export NLP_SK_ENV=<access_key_secret>

   Replace <access_key_id> with your AccessKey ID and <access_key_secret> with your AccessKey secret. For more information about how to obtain an AccessKey ID and an AccessKey secret, see Step 2: Obtain an AccessKey.

3. Configuration on Windows

   1. Create an environment variable file, add the NLP_AK_ENV and NLP_SK_ENV environment variables, and then enter your AccessKey ID and AccessKey secret.

   2. Restart Windows.

Java code sample

/**
 * An AccessKey of an Alibaba Cloud account has full access permissions to all APIs. This poses a high security threat. We strongly recommend that you create and use a RAM user to make API calls or perform routine O&M. To create a RAM user, log on to the RAM console.
 * This example shows how to store the AccessKey ID and AccessKey secret in environment variables. You can also store them in a configuration file as needed.
 * To prevent security threats from key leaks, do not hard-code your AccessKey ID and AccessKey secret in your code.
 */
String accessKeyId = System.getenv("NLP_AK_ENV");
String accessKeySecret = System.getenv("NLP_SK_ENV");
DefaultProfile defaultProfile = DefaultProfile.getProfile("cn-hangzhou",accessKeyId,accessKeySecret);
IAcsClient client = new DefaultAcsClient(defaultProfile);

Map<String, Object> input = new HashMap();
input.put("content","A vague smell occurs on frequent uphill starts. I am not sure if the clutch plate is faulty. The reverse gear only engages after a full stop.");
input.put("domain","car");
input.put("entity",true);
Map<String, Object> map = new HashMap<>();
map.put("input", input);

RunPreTrainServiceRequest request = new RunPreTrainServiceRequest();
request.setServiceName("aoe-automl-app-car");
request.setPredictContent(JSON.toJSONString(map));
RunPreTrainServiceResponse response = client.getAcsResponse(request);
System.out.println(response.getPredictResult());

Python code sample

# Install dependencies
pip install aliyun-python-sdk-core
pip install aliyun-python-sdk-nlp-automl

# -*- coding: utf8 -*-
import json
import os

from aliyunsdkcore.client import AcsClient
from aliyunsdkcore.acs_exception.exceptions import ClientException
from aliyunsdkcore.acs_exception.exceptions import ServerException
from aliyunsdknlp_automl.request.v20191111 import RunPreTrainServiceRequest

"""
An AccessKey of an Alibaba Cloud account has full access permissions to all APIs. This poses a high security threat. We strongly recommend that you create and use a RAM user to make API calls or perform routine O&M. To create a RAM user, log on to the RAM console.
This example shows how to store the AccessKey ID and AccessKey secret in environment variables. You can also store them in a configuration file as needed.
To prevent security threats from key leaks, do not hard-code your AccessKey ID and AccessKey secret in your code.
"""
access_key_id = os.environ['NLP_AK_ENV']
access_key_secret = os.environ['NLP_SK_ENV']

# Initialize AcsClient instance
client = AcsClient(
  access_key_id,
  access_key_secret,
  "cn-hangzhou"
);

content = 'A vague smell occurs on frequent uphill starts. I am not sure if the clutch plate is faulty. The reverse gear only engages after a full stop.'
domain = 'car'
input_params = {
    "input": {
        "content": content,
        "domain": domain,
        "entity": True
    }
}

# Initialize a request and set parameters
request = RunPreTrainServiceRequest.RunPreTrainServiceRequest()
request.set_ServiceName('aoe-automl-app-car')
request.set_PredictContent(json.dumps(input_params))

# Print response
response = client.do_action_with_exception(request)
resp_obj = json.loads(response)
predict_result = json.loads(resp_obj['PredictResult'])
print(json.dumps(predict_result['data']))

Sample PredictContent

The PredictContent parameter is a JSON string, as shown in the following example.

{
  "input": {
    "content": "A vague smell occurs on frequent uphill starts. I am not sure if the clutch plate is faulty. The reverse gear only engages after a full stop.",
    "domain": "car",
    "entity": true
  }
}

Request parameters

Table of supported properties

Sample PredictResult

{
  "code": 1000,
  "data": {
    "cost": "39.912ms",
    "textProb": 0.9975,
    "aspectItem": [
      {
        "clause": "A vague smell occurs on frequent uphill starts",
        "clauseIndex": "0,10",
        "aspectPolarity": "Negative",
        "terms": [
          {
            "aspectTerm": "frequent uphill starts",
            "opinionTerm": "has a vague smell",
            "normedAspectTerm": "frequent uphill starts",
            "normedOpinionTerm": "has a vague smell"
          }
        ],
        "positiveProb": 0.003,
        "aspectCategory": "Odor/Smell",
        "negativeProb": 0.996
      },
      {
        "clause": "The reverse gear only engages after a full stop",
        "clauseIndex": "25,33",
        "aspectPolarity": "Negative",
        "terms": [
          {
            "aspectTerm": "reverse gear",
            "opinionTerm": "only engages after a full stop",
            "normedAspectTerm": "reverse gear",
            "normedOpinionTerm": "only engages after a full stop"
          }
        ],
        "positiveProb": 0.001,
        "aspectCategory": "Gear shifting",
        "negativeProb": 0.999
      }
    ],
    "textPolarity": "Negative"
  },
  "message": "SUCCESS",
  "tracerId": "1639036027.4482515"
}

Response parameters