更新时间:2020-10-19 15:32
商品标题类目预测服务适用于针对电商场景的商品标题,预测所属的类目,类目体系和淘宝一致。使用示例如下。
Java代码示例
DefaultProfile defaultProfile = DefaultProfile.getProfile("cn-hangzhou","your-access-id-key","your-access-id-secret");
IAcsClient client = new DefaultAcsClient(defaultProfile);
Map<String, Object> map = new HashMap<>();
map.put("input", "壁纸");
map.put("topk", 1);
RunPreTrainServiceRequest request = new RunPreTrainServiceRequest();
request.setServiceName("NLP-E-Commerce-Category");
request.setPredictContent(JSON.toJSONString(map));
RunPreTrainServiceResponse response = client.getAcsResponse(request);
System.out.println(response.getPredictResult());
Python代码示例
# 安装依赖
pip install aliyun-python-sdk-core
pip install aliyun-python-sdk-nlp-automl
# -*- coding: utf8 -*-
import json
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
# Initialize AcsClient instance
client = AcsClient(
"<your-access-key-id>",
"<your-access-key-secret>",
"cn-hangzhou"
);
content ={"input": "壁纸","topk":1}
# Initialize a request and set parameters
request = RunPreTrainServiceRequest.RunPreTrainServiceRequest()
request.set_ServiceName('NLP-E-Commerce-Category')
request.set_PredictContent(json.dumps(content))
# Print response
response = client.do_action_with_exception(request)
resp_obj = json.loads(response)
predict_result = json.loads(resp_obj['PredictResult'])
print(predict_result['result'])
PredictContent内容示例
{
"input": "壁纸",
"topk":1
}
PredictResult内容示例
{
"label": [
{
"score": 0.8,
"key": "家装主材-墙纸-纯纸墙纸",
"id":"27-50013322-50024689"
}
]
}
入参说明
参数 | 说明 |
---|---|
input | 商品标题 |
topk | 必填,数字类型,返回指定数量的预测类目,概率从高到低 |
出参说明
参数 | 说明 |
---|---|
key | 识别到的类目,层次结构,结构为一级类目[-二级类目-三级类目-四级类目-叶子类目],最少为一级类目,最多为五级类目 |
id | key对应的ID |
score | 预测类目的概率,数字范围为(0-1]之间 |
在文档使用中是否遇到以下问题
更多建议
匿名提交