|
@@ -38,10 +38,6 @@ func ConfrimTargetMedicalClass(name string) string {
|
|
|
//计算相似度得分
|
|
|
func calculateSimilarityScore(indexDocs map[int][]string, itemArr []string) string {
|
|
|
scoreDocs := map[int]float64{}
|
|
|
- //临时记录~
|
|
|
- scoreDocs_1 := map[int]float64{}
|
|
|
- scoreDocs_2 := map[int]float64{}
|
|
|
-
|
|
|
itemName := strings.Join(itemArr, "")
|
|
|
for k, v := range indexDocs {
|
|
|
v_str := strings.Join(v, "")
|
|
@@ -53,9 +49,6 @@ func calculateSimilarityScore(indexDocs map[int][]string, itemArr []string) stri
|
|
|
finally_score := (base_score + dice_score) / 2
|
|
|
if finally_score >= 0.55 && dice_score > 0.0 {
|
|
|
scoreDocs[k] = qu.FloatFormat(finally_score, 2)
|
|
|
- //临时记录一下分数
|
|
|
- scoreDocs_1[k] = qu.FloatFormat(base_score, 2)
|
|
|
- scoreDocs_2[k] = qu.FloatFormat(dice_score, 2)
|
|
|
}
|
|
|
}
|
|
|
if len(scoreDocs) == 0 {
|
|
@@ -65,20 +58,6 @@ func calculateSimilarityScore(indexDocs map[int][]string, itemArr []string) stri
|
|
|
index, _ := getMaxScore(scoreDocs)
|
|
|
match_str := strings.Join(ul.NgrmDocIndex[index], "")
|
|
|
med_code := ul.ProductDocText[match_str]
|
|
|
- //临时~测试保存数据
|
|
|
- //catalog := ul.CodeCatalog[med_code]
|
|
|
- //ul.Mgo.Save("zzzzzz", map[string]interface{}{
|
|
|
- // "name": strings.Join(itemArr, ""),
|
|
|
- // "match_name": match_str,
|
|
|
- // "score": score,
|
|
|
- // "score_1": scoreDocs_1[index],
|
|
|
- // "score_2": scoreDocs_2[index],
|
|
|
- // "code": med_code,
|
|
|
- // "class_1": catalog["class_1"],
|
|
|
- // "class_2": catalog["class_2"],
|
|
|
- // "class_3": catalog["class_3"],
|
|
|
- // "class_4": catalog["class_4"],
|
|
|
- //})
|
|
|
return med_code
|
|
|
}
|
|
|
|