SimilaritySolutionVersion - Global

concept australia Updated Sep 10, 2026 7 min read SimilaritySolutionVersionAPI.md
Raw file servicenow.com

The SimilaritySolutionVersion API is a scriptable object used in Predictive Intelligence stores.

This API requires the Predictive Intelligence plugin (com.glide.platform_ml) and is provided within the sn_ml namespace.

This API is used is used for working with solution versions based on SimilaritySolution API objects in the SimilaritySolution store.

The system creates a solution version each time you train a solution definition. Most versions are created during scheduled solution training.

Methods in this API are accessible using the following SimilaritySolution methods:

Parent Topic:Server API reference

SimilaritySolutionVersion - getProperties()

Gets solution object properties and version number.

Name Type Description
None

Type

Description

Object

Contents of the Dataset and SimilaritySolution version details. Results vary by object property setup.``` { "domainName": "String", "isActive": "String", "label": "String", "lookupDatasetProperties": {Object}, "name": "String", "predictedFieldName": "String", "processingLanguage": "String", "scope": "String", "stopwords": [Array], "testDatasetProperties": {Object}, "trainingFrequency": "String", "updateFrequency": "String", "versionNumber": "String" }

Text
</td></tr><tr><td>
&lt;Object&gt;.domainName
</td><td>
Domain name associated with this dataset. See [Domain separation and Predictive Intelligence](https://raw.githubusercontent.com/ServiceNow/ServiceNowDocs/australia/markdown/intelligent-experiences/domain-separation-predictive-intelligence.md).Type: String
</td></tr><tr><td>
&lt;Object&gt;.isActive
</td><td>
Flag that indicates whether this version is active.Valid values:
-   true: Version is active.-   false: Version is not active.
 Data type: String
</td></tr><tr><td>
&lt;Object&gt;.label
</td><td>
Identifies the prediction task. ```{  "label": "my first prediction"}

Data type: String.

<Object>.lookupDatasetProperties

Details of the DatasetDefinition() object used as the lookup set. ``` { "encodedQuery": "String", "fieldDetails": [Array], "fieldNames": [Array], "tableName": "String" }

Text
 Data type: Object.
</td></tr><tr><td>
&lt;Object&gt;.lookupDatasetProperties.tableName
</td><td>
Name of the table for the dataset. For example, `"tableName" : "Incident"`. Data type: String.
</td></tr><tr><td>
&lt;Object&gt;.lookupDatasetProperties.fieldNames
</td><td>
List of field names from the specified table as strings. For example, `"fieldNames" : ["short_description", "priority"]`. Data type: Array.
</td></tr><tr><td>
&lt;Object&gt;.lookupDatasetProperties.fieldNames.fieldDetails
</td><td>
List of JavaScript objects that specify field properties. ```[  {    "name": "String",    "type": "String"  }]

Data type: Array.

<Object>.lookupDatasetProperties.fieldNames.fieldDetails.<object>.name

Name of the field defining the type of information to restrict this dataset to. Data type: String.

<Object>.lookupDatasetProperties.fieldDetails.<object>.type

Machine-learning field type. Data type: String.

<Object>.lookupDatasetProperties.fieldDetails.encodedQuery

Encoded query string in the standard platform format. See Encoded query strings.Data type: String.

<Object>.name

System-assigned name. Data type: String.

<Object>.predictedFieldName

Identifies a field to be trained for predictability. Data type: String.

<Object>.processingLanguage

Processing language in two-letter ISO 639-1 language code format. Data type: String.

<Object>.scope

Object scope. Currently the only valid value is global.Data type: String

<Object>.stopwords

Optional. Preset list of strings that the system automatically generates based on the language property setting. For details, see Create a custom stopwords list. Data type: Array.

<Object>.testDatasetProperties

Details of the DatasetDefinition() object used to retrieve similarities between results searched in this model and results found in the lookupDataset. ``` { "encodedQuery": "String", "fieldDetails": [Array], "fieldNames": [Array], "tableName": "String" }

Text
 Data type: Object.
</td></tr><tr><td>
&lt;Object&gt;.testDatasetProperties.tableName
</td><td>
Name of the table for the dataset. For example, `"tableName" : "Incident"`. Data type: String.
</td></tr><tr><td>
&lt;Object&gt;.testDatasetProperties.fieldNames
</td><td>
List of field names from the specified table as strings. For example, `"fieldNames" : ["short_description", "priority"]`. Data type: Array.
</td></tr><tr><td>
&lt;Object&gt;.testDatasetProperties.fieldNames.fieldDetails
</td><td>
List of JavaScript objects that specify field properties. ```[  {    "name": "String",    "type": "String"  }]

Data type: Array.

<Object>.testDatasetProperties.fieldNames.fieldDetails.<object>.name

Name of the field defining the type of information to restrict this dataset to. Data type: String.

<Object>.testDatasetProperties.fieldDetails.<object>.type

Machine-learning field type. Data type: String.

<Object>.testDatasetProperties.fieldDetails.encodedQuery

Encoded query string in the standard platform format. Data type: String.

<Object>.trainingFrequency

The frequency to retrain the model. Possible values:

  • every_30_days
  • every_60_days
  • every_90_days
  • every_120_days
  • every_180_days
  • run_once

Default: run_once

Data type: String.

<Object>.updateFrequency

The frequency at which the model for the solution definition must be rebuilt. Possible values:

  • do_not_update
  • every_1_day
  • every_1_hour
  • every_6_hours
  • every_12_hours
  • every_1_minute
  • every_15_minutes
  • every_30_minutes

Default: do_not_update

Datatype: String

<Object>.versionNumber

Version number of the SimilaritySolution object.Data type: String.
The following example gets properties of the active object version in the store.
JavaScript
// Get propertiesvar mlSolution = sn_ml.SimilaritySolutionStore.get('ml_x_snc_global_similarity_solution');
gs.print(JSON.stringify(JSON.parse(mlSolution.getActiveVersion().getProperties()), null, 2));

Output:

CSS
*** Script: {  "domainName": "global",  "isActive": "true",  "label": "similarity",  "lookupDatasetProperties": {    "encodedQuery": "",    "fieldNames": [      "short_description"    ],    "tableName": "incident"  },  "name": "ml_x_snc_global_global_similarity",  "processingLanguage": "en",  "stopwords": [    "Default English Stopwords"  ],  "testDatasetProperties": {    "fieldNames": [      "short_description"    ],    "tableName": "incident"  },  "versionNumber": "3"}

SimilaritySolutionVersion - getStatus(Boolean includeDetails)

Gets training completion status.

Name

Type

Description

includeDetails

Boolean

Flag that indicates whether to return status details.Valid values:

  • true: Return additional details.
  • false: Don't return additional details.

Default: False

Type

Description

Object

JavaScript object containing training status information for a SimilaritySolution object.``` { "state": "String", "percentComplete": "Number as a String", "hasJobEnded": "Boolean value as a String", "details": {Object} }

Text
</td></tr><tr><td>
&lt;Object&gt;.state
</td><td>
Training completion state. If the training job reaches a terminal state, the job does not leave that state. If the state is terminal, the **hasJobEnded** property is set to `true`.Possible values:
-   `fetching_files_for_training`-   `preparing_data`-   `retry`-   `solution_cancelled` \(terminal\)-   `solution_complete`\(terminal\)-   `solution_error` \(terminal\)-   `solution_incomplete`-   `training_request_received`-   `training_request_timed_out` \(terminal\)-   `training_solution`-   `uploading_solution`-   `waiting_for_training`
Data type: String
</td></tr><tr><td>
&lt;Object&gt;.hasJobEnded
</td><td>
Flag that indicates whether training is complete.Valid values:
-   true: Training is complete.-   false: Training is incomplete.
Data type: Boolean value as a String
</td></tr><tr><td>
&lt;Object&gt;.percentComplete
</td><td>
Training percent complete. If the completion percentage is less than 100, the job might be in a terminal state. For example, if training times out.Data type: Number as a String
Range: 0 thru 100
</td></tr><tr><td>
&lt;Object&gt;.details
</td><td>
Object containing a list of additional training details.Data type: Object
</td></tr></tbody></table>The following example shows a successful result with training complete.

// Get status var mlSolution = sn_ml.SimilaritySolutionStore.get('ml_x_snc_global_similarity_solution');

gs.print(JSON.stringify(JSON.parse(mlSolution.getActiveVersion().getStatus(true), null, 2)));

Text
Output:

{ "state":"solution_complete", "percentComplete":"100", "hasJobEnded":"true", "details":{"stepLabel":"Solution Complete"} // This information is only returned if getStatus(true); }

Text
The following example shows an unsuccessful result with training complete.

// Get status var solutionName = 'ml_x_snc_global_global_similarity_solution'; var mlSolution = sn_ml.SimilaritySolutionStore.get(solutionName); var trainingStatus = JSON.parse(mlSolution.getLatestVersion().getStatus());

gs.print(JSON.stringify(JSON.parse(trainingStatus), null, 2));

Text
Output:

{ "state":"solution_error", "percentComplete":"100", "hasJobEnded":"true" }

Text
## SimilaritySolutionVersion - getVersionNumber\(\)
Gets the version number of a solution object.
|Name|Type|Description||----|----|-----------||None| | |
|Type|Description||----|-----------||String|Version number.|
The following example shows how to get a version number.

// Get version number var mlSolution = sn_ml.SimilaritySolutionStore.get('ml_x_snc_global_similarity_solution');

gs.print("Version number: "+JSON.stringify(JSON.parse(mlSolution.getActiveVersion().getVersionNumber()), null, 2));

Text
Output:

Version number: 1

Text
## SimilaritySolutionVersion - predict\(Object input, Object options\)
Gets the input data for a prediction.
<table id="table_wwz_pbw_plb" class="parameters"><thead><tr><th>
Name
</th><th>
Type
</th><th>
Description
</th></tr></thead><tbody><tr><td>
input
</td><td>
Object
</td><td>
[GlideRecord](https://raw.githubusercontent.com/ServiceNow/ServiceNowDocs/australia/markdown/australia/api-reference/server-api-reference/c_GlideRecordAPI.md) or array of JSON objects containing field names and values as key-value pairs.
</td></tr><tr><td>
options
</td><td>
Object
</td><td>
Optional values for filtering prediction results.```{  "apply_threshold": Boolean,  "top_n": Number}

options.apply_threshold

Boolean

Flag that indicates whether to check the threshold value for the solution and apply it to the result set.Valid values:

  • true: Return results in which confidence is greater than threshold.
  • false: Return all results.

Default: True

options.top_n

Number

If provided, returns the top results, up to the specified number of predictions.

Type

Description

Object

JSON object containing the prediction results sorted by sys_id or record_number. ``` { : [Array] }

Text
</td></tr><tr><td>
&lt;Object&gt;.&lt;identifier&gt;
</td><td>
List of objects with details for each prediction result.Data type: Array of Objects

: [ { "confidence": Number, "predictedSysId": "String", "predictedValue": "String", "threshold": Number } ]

Text
</td></tr><tr><td>
&lt;Object&gt;.&lt;identifier&gt;.&lt;object&gt;.confidence
</td><td>
Value of the confidence associated with the prediction. For example, 53.84. Data type: Number
</td></tr><tr><td>
&lt;Object&gt;.&lt;identifier&gt;.&lt;object&gt;.predictedSysId
</td><td>
The sys\_id of the predicted value. Results can be from any table on which information is being predicted. Data type: String
</td></tr><tr><td>
&lt;Object&gt;.&lt;identifier&gt;.&lt;object&gt;.predictedValue
</td><td>
Value representing the prediction result. Data type: String
</td></tr><tr><td>
&lt;Object&gt;.&lt;identifier&gt;.&lt;object&gt;.threshold
</td><td>
Value of the configured threshold associated with the prediction. Data type: Number
</td></tr></tbody></table>The following example shows how to display prediction results for a predict\(\) method that takes a GlideRecord by sys\_id for input and includes optional parameters to restrict to top three results and exclude the threshold value.

var mlSolution = sn_ml.SimilaritySolutionStore.get('ml_x_snc_global_similarity_solution');

// single GlideRecord input var input = new GlideRecord("incident"); input.get("<sys_id>");

// configure optional parameters var options = {}; options.top_n = 3; options.apply_threshold = false;

var results = mlSolution.getVersion(1).predict(input, options); // pretty print JSON results gs.print(JSON.stringify(JSON.parse(results), null, 2));

Text

{ "<sys_id/now_GR>": [ { "confidence": 62.10782320780268, "threshold": 20.36, "predictedValue": "Clone Issues", "predictedSysId": "" }, { "confidence": 6.945237375770391, "threshold": 16.63, "predictedValue": "Instance Administration", "predictedSysId": "" }, { "confidence": 5.321061076300759, "threshold": 23.7, "predictedValue": "Administration", "predictedSysId": "" } ] }

CSS
The following example shows how to display prediction results for a predict\(\) method that takes an array of field names as key-value pairs for input and includes optional parameters to restrict to top three results and exclude the threshold value.

var mlSolution = sn_ml.SimilaritySolutionStore.get("ml_x_snc_global_similarity_solution"); // key-value pairs input var input = [{"short_description":"my email is not working"}, {short_description:"need help with password"}]; // configure optional parameters var options = {}; options.top_n = 3; options.apply_threshold = false; var results = mlSolution.predict(input, options); // pretty print JSON results gs.print(JSON.stringify(JSON.parse(results), null, 2));

Text

{ "1": [ { "confidence": 37.5023032262591, "threshold": 10.72, "predictedValue": "Authentication", "predictedSysId": "" }, { "confidence": 24.439964862166583, "threshold": 23.7, "predictedValue": "Administration", "predictedSysId": "" }, { "confidence": 11.736320486031047, "threshold": 100, "predictedValue": "Security", "predictedSysId": "" } ], "2": [ { "confidence": 99, "threshold": 17.77, "predictedValue": "Email", "predictedSysId": "" }, { "confidence": 3.182137005157543, "threshold": 10.72, "predictedValue": "Authentication", "predictedSysId": "" }, { "confidence": 2.8773826570713514, "threshold": -1, "predictedValue": "Email (I/f)", "predictedSysId": "" } ] }

Text
Search documentation
Search document titles and file paths on the australia branch