Create a custom similar case model
Summarize
Summary of Create a Custom Similar Case Model
The custom similar case model in ServiceNow enables users to set up a training model that recognizes similarities between two types of tables by comparing their fields. This model is beneficial for predicting similar records based on predefined criteria and is particularly useful for improving case resolution time in Customer Service Management (CSM).
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Key Features
- Role Requirements: Requires mladmin or admin roles to set up and manage the model.
- Model Setup: Access the Task Intelligence Admin Console to initiate the model setup and answer guided questions to define the model parameters.
- Training Data: Allows selection of prediction tables and training tables, along with the relevant fields to optimize training and prediction accuracy.
- Minimum Records: Requires a minimum of 10,000 records for effective training; users can refresh conditions if this threshold is not met.
- Prediction Preferences: Offers flexible prediction options, allowing users to recommend, monitor, or disable predictions based on case sensitivity.
Key Outcomes
Upon successful setup and training of the model, users can view sample results to assess predicted similar records. The model allows for manual or automatic retraining, ensuring it remains effective over time. Once satisfied with the performance, users can deploy the model, enabling proactive case management that enhances efficiency and resolution times.
Set up a training model to help it recognize similarities between two types of tables by comparing their fields.
The model looks at the prediction fields of a prediction table and the training fields of a training table. It uses the similarities in these fields to predict similar records.
- Before you begin
- Role required: ml_admin, admin
- About this task
- The case similarity model is pre-trained with a large data set to learn communication patterns. You select a set of records to test the model and then view the results before deploying.
Set up similar cases prediction model
Use Task Intelligence for CSM to set up similar case prediction model and train it with your data to make predictions. Access your model's performance results, set the prediction preferences and behavior, and deploy your model.
- Navigate to to access the Task Intelligence Admin Console.
- On the Suggest similar case to reduce resolution time card, select Set up model.
This action opens the model and displays the introductory pages. Each page in the model asks you questions and helps you select the information needed to build an effective model.
Train the similarity model
Train your similar case model with training data to predict the similar records by recognizing similarities between fields of Case table and training tables. When you train a machine learning model, the model looks at the prediction fields of a prediction table and the training fields of a training table. It uses the similarities in these fields to predict similar records.
- Enter a name for the model.
- Select the Prediction table you want the model to predict.
- Select Conditions to choose a set of records to use for training.Note:These conditions provide the requirements that a record must meet to make the predictions. However, this functionality is currently not supported.
- Select the Prediction fields which will be used to predict similar records.
- Select the Training table in the training data that you want the model to use to make predictions.
- Select Conditions to choose a set of records to use for training.
- Select the Training fields that you want the model to use to make predictions.
- Select the Language in which training takes place.
- Select the Update Frequency to decide how frequently the training should occur.
- Review the resulting Number of records in the training data based on the selected conditions.
The records that are counted include the number of fields, parameters, and data that the model uses to train. Based on the provided information and the set conditions, the number or records gets updated automatically. The model needs a minimum of 10,000 records for effective training. If this minimum number hasn't been reached, try selecting different conditions. You can also click the refresh icon to refresh the number.
- Select to retain a model manually or set it to auto retrain.
- Select Launch training.
Assess the similarity model
- Recommend similar records for the cases.
- Monitor and run the prediction model for the cases in the background only. Admin can track the predictions made by model by going to .
- Turn off the predictions for the cases.
- View the number value in the Estimated number of records used for training section.
- Select View sample results to see the similar records predicted for each case.
- Choose one of the following options from the Prediction preference drop-down list for each field.
Options Description Recommendations Shows the top recommendations based on the similarity patterns. Agents can choose to accept or reject the recommendation. You can configure the number of recommended values using Advanced Recommended actions for CSM. For more information, see Configuring the Recommended Actions application. Turn off predictions Stops the model from performing any predictions. Monitor only Monitors and runs the model in the background only without making any predictions on the case form. - Select Save & continue.
Deploy the similarity model
- Review your choices from the previous pages and information about how the model was trained.
- Select Deploy to deploy the model.
A pop-up appears confirming that your model was deployed.