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Normalizar a Pontuação

Você pode normalizar sua pontuação de query $search no intervalo de 0 a 1 nos estágios subsequentes do seu pipeline de agregação. Você pode usar os seguintes estágios após seu estágio $search na seguinte ordem para normalizar a pontuação:

  • $addFields

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

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

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

Os exemplos a seguir demonstram como normalizar a pontuação de algumas das queries de exemplo em relação à collection sample_mflix.movies usando os estágios $addFields e $setWindowFields após o estágio $search . Para saber mais sobre as queries, consulte function exemplos de opção .

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]

Os resultados do Atlas Search contêm as seguintes pontuações:

  • A pontuação modificada para a consulta $search no campo score do estágio $addFields.

  • A pontuação máxima atribuída aos documentos nos resultados do campo maxScore do estágio $setWindowFields .

  • A pontuação normalizada no campo normalizedScore do estágio $addFields , que é calculada dividindo a pontuação modificada em $score pela pontuação máxima em $maxScore usando $divide.

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