在Elasticsearch中按最接近的匹配得分

Question

I have a Elasticsearch::Model on a ActiveRecord::Base model that looks like this

class ArtistGroup < ActiveRecord::Base
  include Elasticsearch::Model
  include Elasticsearch::Model::Callbacks

  FT_REDIS_KEY = "agft"
  has_many :artists

  settings index: { number_of_shards: 5 } do
    mappings dynamic: 'false' do
      indexes :normalized_name, analyzer: 'english'
      indexes :name, analyzer: 'english'
    end
  end

  def as_indexed_json(options={})
    as_json(only: ['normalized_name', 'id', 'name'])
  end
....

When I search by .search('haim') I want the document with name: "Haim" to be returned first before others like "Danielle Haim of Haim", how can I control ES querying to score by closest match?

Answer 1

Elasticsearch returns by default the results sorted by relevance (ie the score of each document).

The way that this score is calculated is based on a set of basic rules combined with some query-specific rules.

The standard similarity algorithm used in Elasticsearch is known as term frequency/inverse document frequency, or TF/IDF, which takes the following factors into account:

• Term frequency: How often does the term appear in the field? The more often, the more relevant. A field containing five mentions of the same term is more likely to be relevant than a field containing just one mention.
• Inverse document frequency: How often does each term appear in the index? The more often, the less relevant. Terms that appear in many documents have a lower weight than more-uncommon terms.
• Field-length norm: How long is the field? The longer it is, the less likely it is that words in the field will be relevant. A term appearing in a short title field carries more weight than the same term appearing in a long content field.

Individual queries may combine the TF/IDF score with other factors such as the term proximity in phrase queries, or term similarity in fuzzy queries.

For a complete description of relevance please refer here: http://www.elasticsearch.org/guide/en/elasticsearch/guide/current/sorting.html