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KStem token filter

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KStem token filter

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Provides KStem-based stemming for the English language. The kstem filter combines algorithmic stemming with a built-in dictionary.

The kstem filter tends to stem less aggressively than other English stemmer filters, such as the porter_stem filter.

The kstem filter is equivalent to the stemmer filter’s light_english variant.

This filter uses Lucene’s KStemFilter.

Example

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The following analyze API request uses the kstem filter to stem the foxes jumping quickly to the fox jump quick:

resp = client.indices.analyze(
    tokenizer="standard",
    filter=[
        "kstem"
    ],
    text="the foxes jumping quickly",
)
print(resp)

response = client.indices.analyze(
  body: {
    tokenizer: 'standard',
    filter: [
      'kstem'
    ],
    text: 'the foxes jumping quickly'
  }
)
puts response

const response = await client.indices.analyze({
  tokenizer: "standard",
  filter: ["kstem"],
  text: "the foxes jumping quickly",
});
console.log(response);

GET /_analyze
{
  "tokenizer": "standard",
  "filter": [ "kstem" ],
  "text": "the foxes jumping quickly"
}

The filter produces the following tokens:

[ the, fox, jump, quick ]

Add to an analyzer

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The following create index API request uses the kstem filter to configure a new custom analyzer.

To work properly, the kstem filter requires lowercase tokens. To ensure tokens are lowercased, add the lowercase filter before the kstem filter in the analyzer configuration.

resp = client.indices.create(
    index="my-index-000001",
    settings={
        "analysis": {
            "analyzer": {
                "my_analyzer": {
                    "tokenizer": "whitespace",
                    "filter": [
                        "lowercase",
                        "kstem"
                    ]
                }
            }
        }
    },
)
print(resp)

response = client.indices.create(
  index: 'my-index-000001',
  body: {
    settings: {
      analysis: {
        analyzer: {
          my_analyzer: {
            tokenizer: 'whitespace',
            filter: [
              'lowercase',
              'kstem'
            ]
          }
        }
      }
    }
  }
)
puts response

const response = await client.indices.create({
  index: "my-index-000001",
  settings: {
    analysis: {
      analyzer: {
        my_analyzer: {
          tokenizer: "whitespace",
          filter: ["lowercase", "kstem"],
        },
      },
    },
  },
});
console.log(response);

PUT /my-index-000001
{
  "settings": {
    "analysis": {
      "analyzer": {
        "my_analyzer": {
          "tokenizer": "whitespace",
          "filter": [
            "lowercase",
            "kstem"
          ]
        }
      }
    }
  }
}

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