elasticsearch custom scoring based on date field

To implement custom scoring based on a date field in Elasticsearch, you can use the function_score query. The function_score query allows you to modify the score of documents based on a variety of factors, including date fields. You can define custom scoring functions that consider the date field's value and apply different scoring logic based on your requirements.

Here's an example of how to use function_score for custom scoring based on a date field:

jsonCopy code
{
  "query": {
    "function_score": {
      "query": {
        "match": {
          "your_text_field": "search query"
        }
      },
      "functions": [
        {
          "exp": {
            "your_date_field": {
              "origin": "now",
              "scale": "30d",  // Adjust the scale to change the time decay factor
              "offset": "7d", // Optional offset to control the decay function
              "decay": 0.5     // Custom decay factor, adjust as needed
            }
          }
        }
      ],
      "score_mode": "multiply",
      "boost_mode": "multiply"
    }
  }
}

In this example, we use the function_score query with an exp function to apply a custom scoring function based on a date field called your_date_field. The exp function uses an exponential decay function to adjust the score based on the age of the date field relative to the current date.

The origin parameter sets the reference date for calculating the decay. In this case, it's set to "now" to use the current date as the reference point.

The scale parameter controls the time decay factor. In the example, we set it to "30d", which means the score will decay over 30 days.

The offset parameter is optional and allows you to control the decay function's offset. For example, if you want the decay to start after a specific duration from the origin, you can set an offset.

The decay parameter sets the custom decay factor. You can adjust this value based on how fast or slow you want the score to decay.

The score_mode parameter defines how the scores from the query and functions are combined. In this example, we use "multiply" to multiply the scores together.

The boost_mode parameter defines how the combined score is applied to the final result. In this example, we use "multiply" to apply the custom score as a multiplier to the document's original score.

You can customize the function_score query further based on your specific requirements. By adjusting the decay factor and other parameters, you can fine-tune the custom scoring based on the date field to achieve the desired relevance in your search results.