TF-IDF and BM25 scoring in Elasticsearch - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to set the similarity to BM25 in the Elasticsearch index settings.

Elasticsearch

{
  "settings": {
    "similarity": {
      "default": {
        "type": "[1]"
      }
    }
  }
}

Drag options to blanks, or click blank then click option'

Abm25

Btfidf

Cclassic

Dboolean

Attempts:

3 left

💡 Hint

Common Mistakes

Using "tfidf" which is not a valid similarity type in Elasticsearch.

Using "classic" which refers to TF-IDF but is deprecated.

Using "boolean" which is a different similarity model.

BM25 is the default and recommended similarity algorithm in Elasticsearch for scoring.

2fill in blank

medium

Complete the query to use the classic TF-IDF similarity for a specific field.

Elasticsearch

{
  "mappings": {
    "properties": {
      "content": {
        "type": "text",
        "similarity": "[1]"
      }
    }
  }
}

Drag options to blanks, or click blank then click option'

Abm25

Btfidf

Cboolean

Dclassic

Attempts:

3 left

💡 Hint

Common Mistakes

Using "tfidf" which is not a valid similarity type in Elasticsearch.

Using "bm25" which is the default but not TF-IDF.

Using "boolean" which is a different similarity model.

The "classic" similarity uses the TF-IDF scoring model in Elasticsearch.

3fill in blank

hard

Fix the error in the BM25 parameter setting to adjust the k1 parameter.

Elasticsearch

{
  "settings": {
    "similarity": {
      "my_bm25": {
        "type": "bm25",
        "k1": [1]
      }
    }
  }
}

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A1.2

Btrue

Ck1

D"1.2"

Attempts:

3 left

💡 Hint

Common Mistakes

Putting the number in quotes making it a string.

Using the parameter name as the value.

Using boolean values instead of numbers.

The k1 parameter must be a numeric value, not a string or other type.

4fill in blank

hard

Fill both blanks to create a custom similarity with BM25 and set the b parameter.

Elasticsearch

{
  "settings": {
    "similarity": {
      "custom_bm25": {
        "type": "[1]",
        "b": [2]
      }
    }
  }
}

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Abm25

Bclassic

C0.75

D1.5

Attempts:

3 left

💡 Hint

Common Mistakes

Using "classic" instead of "bm25" for the similarity type.

Setting b to a value greater than 1 or as a string.

Confusing b with k1 parameter.

BM25 similarity type is "bm25" and the b parameter controls length normalization, commonly set to 0.75.

5fill in blank

hard

Fill all three blanks to define a custom BM25 similarity with k1 and b parameters and apply it to a field.

Elasticsearch

{
  "settings": {
    "similarity": {
      "custom_bm25": {
        "type": "[1]",
        "k1": [2],
        "b": [3]
      }
    }
  },
  "mappings": {
    "properties": {
      "description": {
        "type": "text",
        "similarity": "custom_bm25"
      }
    }
  }
}

Drag options to blanks, or click blank then click option'

Abm25

B1.2

C0.75

Dclassic

Attempts:

3 left

💡 Hint

Common Mistakes

Using "classic" instead of "bm25" for the type.

Putting numeric parameters in quotes.

Omitting the similarity setting in the field mapping.

Custom BM25 similarity requires type "bm25" and numeric parameters k1 and b, commonly 1.2 and 0.75 respectively.