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Customize the Score in Results

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  • Behavior
  • Options
  • boost
  • Fields
  • Examples
  • constant
  • Examples
  • embedded
  • Fields
  • Examples
  • function
  • Expressions
  • Examples

Every document returned by an Atlas Search query is assigned a score based on relevance, and the documents included in a result set are returned in order from highest score to lowest.

Many factors can influence a document's score, including:

  • The position of the search term in the document,

  • The frequency of occurrence of the search term in the document,

  • The type of operator the query uses,

  • The type of analyzer the query uses.

The score assigned to a returned document is part of the document's metadata. You can include each returned document's score along with the result set by using a $project in your aggregation pipeline. After a $project stage, you do not need to include a descending $sort because Atlas Search returns the documents from highest score to lowest by default.

The following example query uses a $project stage to add a field named score to the returned documents:

1db.movies.aggregate([
2 {
3 $search: {
4 "text": {
5 "query": "Helsinki",
6 "path": "plot"
7 }
8 }
9 },
10 {
11 $project: {
12 plot: 1,
13 title: 1,
14 score: { $meta: "searchScore" }
15 }
16 }
17])

More information about the Lucene scoring algorithm can be found in the Lucene documentation.

The following score modifying options are available to all operators. For details and examples, click any of the following options:

The boost option multiplies a result's base score by a given number or the value of a numeric field in the documents. For example, you can use boost to increase the importance of certain matching documents in the result.

Note

  • The boost and constant options can't be used together.

  • The boost option with path is the same as multiplying using the function option with a path expression.

The boost option takes the following fields:

Field
Type
Necessity
Description
value
float
Conditional
Number to multiply the default base score by. Value must be a positive number. Either value or path is required, but you can't specify both.
path
string
Conditional
Name of the numeric field whose value to multiply the default base score by. Either path or value is required, but you can't specify both.
undefined
float
Optional
Numeric value to substitute for path if the numeric field specified through path is not found in the documents. If omitted, defaults to 0. You can specify this only if you specify path.

The following examples use the movies collection in the sample_mflix database. If you have the sample dataset on your cluster, you can create the Atlas Search default index and run the example queries on your cluster.

The sample compound queries demonstrate how to increase the importance of one search criteria over another. The queries include a $project stage to exclude all fields except title and score.

The constant option replaces the base score with a specified number.

Note

The constant and boost options may not be used together.

The following example uses the default index on the sample_mflix.movies collection to query the plot and title fields using the compound operator. In the query, the text operator uses score with the constant option to replace all score results with 5 for results that match the query against the title field only.

1db.movies.aggregate([
2 {
3 $search: {
4 "compound": {
5 "should": [{
6 "text": {
7 "query": "tower",
8 "path": "plot"
9 }
10 },
11 {
12 "text": {
13 "query": "tower",
14 "path": "title",
15 "score": { "constant": { "value": 5 } }
16 }
17 }]
18 }
19 }
20 },
21 {
22 $project: {
23 "_id": 0,
24 "title": 1,
25 "score": { "$meta": "searchScore" }
26 }
27 }
28])

The above query returns the following results, in which the score for documents that match the query against the title field only is replaced with the specified constant value:

1[
2 {
3 plot: 'Several months after witnessing a murder, residents of Tower Block 31 find themselves being picked off by a sniper, pitting those lucky enough to be alive into a battle for survival.',
4 title: 'Tower Block',
5 score: 8.15460205078125
6 },
7 {
8 plot: "When a group of hard-working guys find out they've fallen victim to their wealthy employer's Ponzi scheme, they conspire to rob his high-rise residence.",
9 title: 'Tower Heist',
10 score: 5
11 },
12 {
13 plot: 'Toru Kojima and his friend Koji are young student boys with one thing in common - they both love to date older women. Koji is a playboy with several women, young and older, whereas Toru is a romantic with his heart set on on certain lady.',
14 title: 'Tokyo Tower',
15 score: 5
16 },
17 {
18 plot: 'A middle-aged mental patient suffering from a split personality travels to Italy where his two personalities set off all kinds of confusing developments.',
19 title: 'The Leaning Tower',
20 score: 5
21 },
22 {
23 plot: 'A documentary that questions the cost -- and value -- of higher education in the United States.',
24 title: 'Ivory Tower',
25 score: 5
26 }
27]

Note

This option can be used with embeddedDocument operator only.

The embedded option allows you to configure how to:

  • Aggregate scores of multiple matching embedded documents

  • Modify the score of an embeddedDocument operator after aggregating scores from matching embedded documents

Note

The Atlas Search embeddedDocuments index option, embeddedDocument operator, and embedded scoring option are in preview. When an Atlas Search index on a replica set or single MongoDB shard reaches Lucene’s two billion document limit, Atlas Search doesn't index new documents or apply updates to existing documents for that index. A solution to accomodate this limitation will be in place when we make this feature generally available. Meanwhile, the MongoDB Cloud Support team will help troubleshoot any issues related to using this feature as part of your contract.

The embedded option takes the following fields:

Field
Type
Necessity
Description
aggregate
string
Optional

Configures how to combine scores of matching embedded documents. Value must be one of the following aggregation strategies:

  • sum - (Default) Sum the score of all matching embedded documents.

  • maximum - Choose the greatest score of all matching embedded documents.

  • minimum - Choose the least high score of all matching embedded documents.

  • mean - Choose the average (arithmetic mean) score of all matching embedded documents. Atlas Search include scores of matching embedded documents only when computing the average. Atlas Search doesn't count embedded documents that don't satisfy query predicates as documents with scores of zero.

If omitted, defaults to sum.

outerScore
Optional
Specifies the score modification to apply after applying the aggregation strategy.

The following sample query uses an index named default on the sample_analytics.transactions collection. The index configures an embeddedDocuments field on documents in the transactions array, string fields for transactions.symbol and transactions.transaction_code fields, and a number field on the transaction_count field.

The sample query on the transactions field, which contains an array of documents, includes a $limit stage to limit the output to 10 results and a $project stage to:

  • Exclude all fields except account_id and transaction_count.

  • Add a field named score that applies an aggregation strategy and further score modification after.

    Note

    You can use function inside the score option of the embeddedDocument operator's operator. However, for function score expressions that require the path option, the numeric field that you specify as the path for the expression must be inside the embeddedDocument operator's path. For example, in the example query below, the field transactions.amount that is specified inside the score option of the compound operator on line 24 is inside in the embeddedDocument operator's path transactions on line 4.

The query searches for accounts that have bought AMD and multiplies the largest single AMD purchase (by number of shares) by the log1p value of the number of transactions that the account has made in this period. It ranks the accounts based on the following:

  • Number of AMD bought in a single transaction

  • Number of transactions in the last period

1db.transactions.aggregate({
2 "$search": {
3 "embeddedDocument": {
4 "path": "transactions",
5 "operator": {
6 "compound": {
7 "must": [
8 {
9 "text": {
10 "path": "transactions.symbol",
11 "query": "amd"
12 }
13 },
14 {
15 "text": {
16 "path": "transactions.transaction_code",
17 "query": "buy"
18 }
19 }
20 ],
21 "score": {
22 "function": {
23 "path": {
24 "value": "transactions.amount",
25 "undefined": 1.0
26 }
27 }
28 }
29 }
30 },
31 "score": {
32 "embedded": {
33 "aggregate": "maximum",
34 "outerScore": {
35 "function": {
36 "multiply": [
37 {
38 "log1p": {
39 "path": {
40 "value": "transaction_count"
41 }
42 }
43 },
44 {
45 "score": "relevance"
46 }
47 ]
48 }
49 }
50 }
51 }
52 }
53 }
54},
55{ "$limit": 10 },
56{
57 "$project": {
58 "_id": 0,
59 "account_id": 1,
60 "transaction_count": 1,
61 "score": { $meta: "searchScore" }
62 }
63})

Atlas Search ranks accounts that have made many transactions in the last period and bought many AMD in a single transaction highly.

1[
2 { account_id: 467651, transaction_count: 99, score: 19982 },
3 { account_id: 271554, transaction_count: 96, score: 19851.822265625 },
4 { account_id: 71148, transaction_count: 99, score: 19840 },
5 { account_id: 408143, transaction_count: 100, score: 19836.76953125 },
6 { account_id: 977774, transaction_count: 98, score: 19822.64453125 },
7 { account_id: 187107, transaction_count: 96, score: 19754.470703125 },
8 { account_id: 492843, transaction_count: 97, score: 19744.998046875 },
9 { account_id: 373169, transaction_count: 93, score: 19553.697265625 },
10 { account_id: 249078, transaction_count: 89, score: 19436.896484375 },
11 { account_id: 77690, transaction_count: 90, score: 19418.017578125 }
12]

The function option allows you to alter the final score of the document using a numeric field . You can specify the numeric field for computing the final score through an expression. If the final result of the function score is less than 0, Atlas Search replaces the score with 0.

Note

You can use function inside the score option of the embeddedDocument operator's operator. However, for function score expressions that require the path option, the numeric field that you specify as the path for the expression must be inside the embeddedDocument operator's path.

Use the following expressions with the function option to alter the final score of the document:

  • Arithmetic expressions, which add or multiply a series of numbers.

  • Constant expressions, which allow a constant number in the function score.

  • Gaussian decay expressions, which decay, or reduces, the scores by multiplying at a specified rate.

  • Path expressions, which incorporate an indexed numeric field value into a function score.

  • Score expressions, which return the relevance score assigned by Atlas Search.

  • Unary expressions, which are expressions that take a single argument. In Atlas Search, you can calculate the log10(x) or log10(x+1) of a specified number.

The following examples use the default index on the sample_mflix.movies collection to query the title field. The sample queries include a $limit stage to limit the output to 5 results and a $project stage to exclude all fields except title and score.

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