Artificial Intelligence Recommendation:Obtain recommendation results

Overview

This topic describes how to obtain recommendation results from the Artificial Intelligence Recommendation (AIRec) service. If you call an API operation to obtain recommendation results, the data is returned in the JSON format.

The content in this topic is applicable to the AIRec instances of Industry Operation Edition and Algorithm Configuration Edition.

Parameters

Causes of an empty recommendation result:

1. The values of specific request parameters are invalid. Make sure that the value you specified for the scene_id parameter is contained in the uploaded data.

Make sure that the value you specified for the user_id parameter is contained in the user table. If the value you specified for the user_id parameter does not exist in the user table, a new user is created.

Make sure that the number of recommended items is less than the number of items that can be recommended in the specified scenario.

Note: A maximum of 50 recommended items can be returned if a server SDK is used to obtain recommendation results. In a scenario whose recommendation service type is set to related recommendations, you must specify the existing item in the format of item_id:item_type, as shown in the following figure.2. Only a small number of items can meet the recommendation conditions. As a result, after the exposure blocking feature is enabled, no available items can be recommended to users and the recommendation result is empty.

package com.aliyun.airec;

import com.aliyuncs.DefaultAcsClient;
import com.aliyuncs.airec.model.v20181012.RecommendRequest;
import com.aliyuncs.airec.model.v20181012.RecommendResponse;
import com.aliyuncs.http.FormatType;
import com.aliyuncs.profile.DefaultProfile;
import com.aliyuncs.profile.IClientProfile;

public class Recommend {

    public static void main(String args[]) {
        // The AccessKey pair of an Alibaba Cloud account has permissions on all API operations. To avoid security risks, we recommend that you use a RAM user to call API operations or perform routine O&M. 
        // We recommend that you do not save the AccessKey ID and AccessKey secret in your project code. Otherwise, the AccessKey pair may be leaked and the security of all resources within your account may be compromised. 

        // In this example, the AccessKey ID and AccessKey secret are stored in the environment variables to implement identity verification. 
        IClientProfile profile = DefaultProfile.getProfile("cn-hangzhou", System.getenv("ALIBABA_CLOUD_ACCESS_KEY_ID"), System.getenv("ALIBABA_CLOUD_ACCESS_KEY_SECRET"));
        DefaultProfile.addEndpoint("cn-hangzhou", "Airec", "airec.cn-hangzhou.aliyuncs.com");

        DefaultAcsClient client = new DefaultAcsClient(profile);

        RecommendRequest request = new RecommendRequest();

        // You must set the following parameters: 
        request.setInstanceId("airec-xxx");
        request.setReturnCount(10);
        request.setSceneId("Scenario ID");

        // At least one of the following parameters must be reported: 
        request.setUserId("0");
        request.setImei("0");

        // This parameter is optional if the recommendation service type of the scenario is set to related recommendations.
        //request.setItems("88:article,33:image");

        // Set the rankOpen parameter to false and the recType parameter to hot if you need to disable the personalized recommendation feature.
        //request.setRankOpen(false);
        //request.setRecType("hot");

        request.setAcceptFormat(FormatType.JSON);

        try {
            RecommendResponse response = client.getAcsResponse(request);

            for (RecommendResponse.ResultItem item : response.getResult()) {
                System.out.println(item.getItemId());
                System.out.println(item.getItemType());
                System.out.println(item.getTraceId());
                System.out.println(item.getTraceInfo());
                System.out.println(item.getMatchInfo());
                System.out.println(item.getWeight());
                System.out.println(item.getPosition());
            }
        } catch (Exception e) {
            e.printStackTrace();
        }
    }
}