詞幹
stemmer 過濾器可將字詞還原為其基本或字根形式(稱為詞幹化),使其更容易匹配不同轉折中具有類似涵義的字詞。stemmer 過濾器支援多種語言,可在各種語言環境中進行有效的搜尋與索引。
設定
stemmer 篩選器是 Milvus 的自訂篩選器。若要使用它,請在篩選器設定中指定"type": "stemmer" ,以及language 參數,以選擇所需的語言進行詞幹處理。
analyzer_params = {
"tokenizer": "standard",
"filter":[{
"type": "stemmer", # Specifies the filter type as stemmer
"language": "english", # Sets the language for stemming to English
}],
}
Map<String, Object> analyzerParams = new HashMap<>();
analyzerParams.put("tokenizer", "standard");
analyzerParams.put("filter",
Collections.singletonList(
new HashMap<String, Object>() {{
put("type", "stemmer");
put("language", "english");
}}
)
);
const analyzer_params = {
"tokenizer": "standard",
"filter":[{
"type": "stemmer", // Specifies the filter type as stop
"language": "english",
}],
};
analyzerParams = map[string]any{"tokenizer": "standard",
"filter": []any{map[string]any{
"type": "stemmer",
"language": "english",
}}}
# restful
analyzerParams='{
"tokenizer": "standard",
"filter": [
{
"type": "stemmer",
"language": "english"
}
]
}'
stemmer 過濾器接受下列可設定的參數。
參數 |
說明 |
|---|---|
|
指定詞幹處理的語言。支援的語言包括 |
stemmer 過濾器會對 tokenizer 產生的詞彙進行操作,因此必須與 tokenizer 結合使用。
定義analyzer_params 之後,您可以在定義集合模式時,將它們套用到VARCHAR 欄位。這可讓 Milvus 使用指定的分析器來處理該欄位中的文字,以進行有效率的標記化和過濾。詳情請參閱範例使用。
範例
在應用分析器配置到您的收集模式之前,請使用run_analyzer 方法驗證其行為。
分析器配置
analyzer_params = {
"tokenizer": "standard",
"filter":[{
"type": "stemmer", # Specifies the filter type as stemmer
"language": "english", # Sets the language for stemming to English
}],
}
Map<String, Object> analyzerParams = new HashMap<>();
analyzerParams.put("tokenizer", "standard");
analyzerParams.put("filter",
Collections.singletonList(
new HashMap<String, Object>() {{
put("type", "stemmer");
put("language", "english");
}}
)
);
// javascript
analyzerParams = map[string]any{"tokenizer": "standard",
"filter": []any{map[string]any{
"type": "stemmer",
"language": "english",
}}}
# restful
analyzerParams='{
"tokenizer": "standard",
"filter": [
{
"type": "stemmer",
"language": "english"
}
]
}'
驗證使用run_analyzerCompatible with Milvus 2.5.11+
from pymilvus import (
MilvusClient,
)
client = MilvusClient(uri="http://localhost:19530")
# Sample text to analyze
sample_text = "running runs looked ran runner"
# Run the standard analyzer with the defined configuration
result = client.run_analyzer(sample_text, analyzer_params)
print("Standard analyzer output:", result)
import io.milvus.v2.client.ConnectConfig;
import io.milvus.v2.client.MilvusClientV2;
import io.milvus.v2.service.vector.request.RunAnalyzerReq;
import io.milvus.v2.service.vector.response.RunAnalyzerResp;
ConnectConfig config = ConnectConfig.builder()
.uri("http://localhost:19530")
.build();
MilvusClientV2 client = new MilvusClientV2(config);
List<String> texts = new ArrayList<>();
texts.add("running runs looked ran runner");
RunAnalyzerResp resp = client.runAnalyzer(RunAnalyzerReq.builder()
.texts(texts)
.analyzerParams(analyzerParams)
.build());
List<RunAnalyzerResp.AnalyzerResult> results = resp.getResults();
// javascript
import (
"context"
"encoding/json"
"fmt"
"github.com/milvus-io/milvus/client/v2/milvusclient"
)
client, err := milvusclient.New(ctx, &milvusclient.ClientConfig{
Address: "localhost:19530",
APIKey: "root:Milvus",
})
if err != nil {
fmt.Println(err.Error())
// handle error
}
bs, _ := json.Marshal(analyzerParams)
texts := []string{"running runs looked ran runner"}
option := milvusclient.NewRunAnalyzerOption(texts).
WithAnalyzerParams(string(bs))
result, err := client.RunAnalyzer(ctx, option)
if err != nil {
fmt.Println(err.Error())
// handle error
}
# restful
not support yet
預期輸出
['run', 'run', 'look', 'ran', 'runner']