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4. Score Documents

Normalize the Score

You can normalize your $search query score in the range from 0 to 1 in the subsequent stages of your aggregation pipeline. You can use the following stages after your $search stage in the following order to normalize the score:

  • $addFields

    {
      "$addFields": {
        "score": {
          "$meta": "searchScore"
        }
      }
    }

  • $setWindowFields

    {
      "$setWindowFields": {
        "output": {
          "maxScore": {
            "$max": "$score"
          }
        }
      }
    }

  • $addFields

    {
      "$addFields": {
        "normalizedScore": {
          "$divide": [
            "$score", "$maxScore"
          ]
        }
      }
    }

Examples

The following examples demonstrate how to normalize the score for some of the example queries against the sample_mflix.movies collection using the $addFields and $setWindowFields stages after the $search stage. To learn more about the queries, see function option examples.

1db.movies.aggregate([{
2  "$search": {
3    "text": {
4      "query": "Helsinki",
5      "path": "plot"
6    }
7  }
8},
9{
10  "$limit": 5
11},
12{
13  "$project": {
14    "_id": 0,
15    "title": 1,
16    "score": 1,
17    "maxScore": 1,
18    "normalizedScore": 1
19  }
20},
21{
22  "$addFields": {
23    "score": {
24      "$meta": "searchScore"
25    }
26  }
27},
28{
29  "$setWindowFields": {
30    "output": {
31      "maxScore": {
32        "$max": "$score"
33      }
34    }
35  }
36},
37{
38  "$addFields": {
39    "normalizedScore": {
40      "$divide": [
41        "$score", "$maxScore"
42      ]
43    }
44  }
45}])
1[
2  {
3    title: 'Drifting Clouds',
4    score: 4.5660295486450195,
5    maxScore: 4.5660295486450195,
6    normalizedScore: 1
7  },
8  {
9    title: 'Sairaan kaunis maailma',
10    score: 4.041563034057617,
11    maxScore: 4.5660295486450195,
12    normalizedScore: 0.8851372929150143
13  },
14  {
15    title: 'Bad Luck Love',
16    score: 3.6251673698425293,
17    maxScore: 4.5660295486450195,
18    normalizedScore: 0.79394303764817
19  },
20  {
21    title: 'Bad Luck Love',
22    score: 3.6251673698425293,
23    maxScore: 4.5660295486450195,
24    normalizedScore: 0.79394303764817
25  },
26  {
27    title: 'Forbidden Fruit',
28    score: 3.6251673698425293,
29    maxScore: 4.5660295486450195,
30    normalizedScore: 0.79394303764817
31  }
32]
1db.movies.aggregate([{
2  "$search": {
3    "text": {
4      "path": "title",
5      "query": "men",
6      "score": {
7        "function":{
8          "multiply":[
9            {
10              "path": {
11                "value": "imdb.rating",
12                "undefined": 2
13              }
14            },
15            {
16              "score": "relevance"
17            }
18          ]
19        }
20      }
21    }
22  }
23},
24{
25  "$limit": 5
26},
27{
28  "$addFields": {
29    "score": {
30      "$meta": "searchScore"
31    }
32  }
33},
34{
35  "$setWindowFields": {
36    "output": {
37      "maxScore": {
38        "$max": "$score"
39      }
40    }
41  }
42},
43{
44  "$addFields": {
45    "normalizedScore": {
46      "$divide": [
47        "$score", "$maxScore"
48      ]
49    }
50  }
51},
52{
53  "$project": {
54    "_id": 0,
55    "title": 1,
56    "score": 1,
57    "maxScore": 1,
58    "normalizedScore": 1
59  }
60}])
1[
2  {
3    title: 'Men...',
4    score: 23.431293487548828,
5    maxScore: 23.431293487548828,
6    normalizedScore: 1
7  },
8  {
9    title: '12 Angry Men',
10    score: 22.080968856811523,
11    maxScore: 23.431293487548828,
12    normalizedScore: 0.9423708882544255
13  },
14  {
15    title: 'X-Men',
16    score: 21.34803581237793,
17    maxScore: 23.431293487548828,
18    normalizedScore: 0.911090795039637
19  },
20  {
21    title: 'X-Men',
22    score: 21.34803581237793,
23    maxScore: 23.431293487548828,
24    normalizedScore: 0.911090795039637
25  },
26  {
27    title: 'Matchstick Men',
28    score: 21.05954933166504,
29    maxScore: 23.431293487548828,
30    normalizedScore: 0.8987787781692841
31  }
32]
1db.movies.aggregate([{
2  "$search": {
3    "text": {
4      "path": "title",
5      "query": "shop",
6      "score": {
7        "function":{
8          "gauss": {
9            "path": {
10              "value": "imdb.rating",
11              "undefined": 4.6
12            },
13            "origin": 9.5,
14            "scale": 5,
15            "offset": 0,
16            "decay": 0.5
17          }
18        }
19      }
20    }
21  }
22},
23{
24  "$limit": 5
25},
26{
27  "$addFields": {
28    "score": {
29      "$meta": "searchScore"
30    }
31  }
32},
33{
34  "$setWindowFields": {
35    "output": {
36      "maxScore": {
37        "$max": "$score"
38      }
39    }
40  }
41},
42{
43  "$addFields": {
44    "normalizedScore": {
45      "$divide": [
46        "$score", "$maxScore"
47      ]
48    }
49  }
50},
51{
52  "$project": {
53    "_id": 0,
54    "title": 1,
55    "score": 1,
56    "maxScore": 1,
57    "normalizedScore": 1
58  }
59}])
1[
2  {
3    title: 'The Shop Around the Corner',
4    score: 0.9471074342727661,
5    maxScore: 0.9471074342727661,
6    normalizedScore: 1
7  },
8  {
9    title: 'Exit Through the Gift Shop',
10    score: 0.9471074342727661,
11    maxScore: 0.9471074342727661,
12    normalizedScore: 1
13  },
14  {
15    title: 'The Shop on Main Street',
16    score: 0.9395227432250977,
17    maxScore: 0.9471074342727661,
18    normalizedScore: 0.9919917310611205
19  },
20  {
21    title: 'Chop Shop',
22    score: 0.8849083781242371,
23    maxScore: 0.9471074342727661,
24    normalizedScore: 0.9343273488331464
25  },
26  {
27    title: 'Little Shop of Horrors',
28    score: 0.8290896415710449,
29    maxScore: 0.9471074342727661,
30    normalizedScore: 0.8753913353110349
31  }
32]
1db.movies.aggregate([{
2  "$search": {
3    "text": {
4      "path": "title",
5      "query": "men",
6      "score": {
7        "function":{
8          "path": {
9            "value": "imdb.rating",
10            "undefined": 4.6
11          }
12        }
13      }
14    }
15  }
16},
17{
18  "$limit": 5
19},
20{
21  "$addFields": {
22    "score": {
23      "$meta": "searchScore"
24    }
25  }
26},
27{
28  "$setWindowFields": {
29    "output": {
30      "maxScore": {
31        "$max": "$score"
32      }
33    }
34  }
35},
36{
37  "$addFields": {
38    "normalizedScore": {
39      "$divide": [
40        "$score", "$maxScore"
41      ]
42    }
43  }
44},
45{
46  "$project": {
47    "_id": 0,
48    "title": 1,
49    "score": 1,
50    "maxScore": 1,
51    "normalizedScore": 1
52  }
53}])
1[
2  {
3    title: '12 Angry Men',
4    score: 8.899999618530273,
5    maxScore: 8.899999618530273,
6    normalizedScore: 1
7  },
8  {
9    title: 'The Men Who Built America',
10    score: 8.600000381469727,
11    maxScore: 8.899999618530273,
12    normalizedScore: 0.9662922191102197
13  },
14  {
15    title: 'No Country for Old Men',
16    score: 8.100000381469727,
17    maxScore: 8.899999618530273,
18    normalizedScore: 0.9101124414213563
19  },
20  {
21    title: 'X-Men: Days of Future Past',
22    score: 8.100000381469727,
23    maxScore: 8.899999618530273,
24    normalizedScore: 0.9101124414213563
25  },
26  {
27    title: 'The Best of Men',
28    score: 8.100000381469727,
29    maxScore: 8.899999618530273,
30    normalizedScore: 0.9101124414213563
31  }
32]
1db.movies.aggregate([{
2  "$search": {
3    "text": {
4      "path": "title",
5      "query": "men",
6      "score": {
7        "function": {
8          "log": {
9            "path": {
10              "value": "imdb.rating",
11              "undefined": 10
12            }
13          }
14        }
15      }
16    }
17  }
18},
19{
20  "$limit": 5
21},
22{
23  "$addFields": {
24    "score": {
25      "$meta": "searchScore"
26    }
27  }
28},
29{
30  "$setWindowFields": {
31    "output": {
32      "maxScore": {
33        "$max": "$score"
34      }
35    }
36  }
37},
38{
39  "$addFields": {
40    "normalizedScore": {
41      "$divide": [
42        "$score", "$maxScore"
43      ]
44    }
45  }
46},
47{
48  "$project": {
49    "_id": 0,
50    "title": 1,
51    "score": 1,
52    "maxScore": 1,
53    "normalizedScore": 1
54  }
55}])
1[
2  {
3    title: '12 Angry Men',
4    score: 0.9493899941444397,
5    maxScore: 0.9493899941444397,
6    normalizedScore: 1
7  },
8  {
9    title: 'The Men Who Built America',
10    score: 0.9344984292984009,
11    maxScore: 0.9493899941444397,
12    normalizedScore: 0.9843145968064908
13  },
14  {
15    title: 'No Country for Old Men',
16    score: 0.9084849953651428,
17    maxScore: 0.9493899941444397,
18    normalizedScore: 0.9569144408182233
19  },
20  {
21    title: 'X-Men: Days of Future Past',
22    score: 0.9084849953651428,
23    maxScore: 0.9493899941444397,
24    normalizedScore: 0.9569144408182233
25  },
26  {
27    title: 'The Best of Men',
28    score: 0.9084849953651428,
29    maxScore: 0.9493899941444397,
30    normalizedScore: 0.9569144408182233
31  }
32]

The Atlas Search results contain the following scores:

  • The modified score for the $search query in the score field from the $addFields stage.

  • The maximum score assigned to the documents in the results in the maxScore field from the $setWindowFields stage.

  • The normalized score in the normalizedScore field from the $addFields stage, which is computed by dividing the modified score in $score by the maximum score in $maxScore using $divide.

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Return the Score Details