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# BIASVAL

The `BIASVAL` field specifier (case sensitive) allows you to bias the score of result documents by a specified percentage, based on whether they include a specific value in the specified field.

NOTE: You can optimize the speed of this field specifier by restricting the field to one of the following configuration options:

- , when the configuration parameter is set to `True`.

## Format

    FieldText=BIASVAL{fieldValue,percentage,fuzzydistance}:fieldName

`fieldValue` | The value that the specified field must contain to increase or decrease the weight by the `percentage`. You can leave this value empty to apply a score change to any result document that does not have the specified field, or that has the field with an empty value.
`percentage` | A percentage in the range -100 to 100. The percentage (positive or negative) by which to boost the relevance of documents that have the value `fieldValue` in the field `fieldName`. (The boosted relevance score cannot be greater than 100% or less than -100%.) When you set to `True`, this is the absolute value by which to boost the weight and it is then not limited by +/- 100.
`fuzzydistance` | (Optional) An integer that determines a fuzzy matching distance. If you set a fuzzy distance, Knowledge Discovery applies a scaled weighting boost to documents where the field value for the hit document is within this fuzzy distance of the query value. The fuzzy distance corresponds to the `DREFUZZY` tolerance (see ). OpenText recommends that you use a maximum value of 6.
`fieldName` | The name of the field that must be present (and must contain the proper value) for the document relevance to be boosted.

NOTE: `BIASVAL` requires two arguments. `BIASVAL{percentBoost}:fieldName` is not valid syntax.

## Examples

    FieldText=BIASVAL{Cambridge,10}:TOWN

A document whose `TOWN` field value is `Cambridge` has its weighting increased by 10% (although the weighting cannot go over 100%).

    FieldText=BIASVAL{Cambridge,10}:TOWN+BIASVAL{London,-10}:TOWN

A document whose `TOWN` field value is `Cambridge` has its weighting increased by 10%, and a document whose `TOWN` field value is `London` has its weighting decreased by 10%. This example shows that biases can be negative as well as positive, and that you can include more than one set of parameters with the specifier.

    FieldText=BIASVAL{,-10}:COLOUR

A document that does not have the `COLOUR` field, or that has a `COLOUR` field with an empty value, has its weighting decreased by 10%.

    FieldText=BIASVAL{Cambridge,10,2}:TOWN

A document whose `TOWN` field value is `Cambridge` has its weighting increased by 10% (although the weighting cannot go over 100%). If the `TOWN` field value contains a value that is similar to `Cambridge` (within a fuzzy distance of 2), a reduced weighting boost is applied.

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Version 25.1 | Last updated January 2025

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Product: Knowledge Discovery View Component 25.1

Topic Title: BIASVAL