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詞幹提取器

stemmer 篩選器可將單字還原為其基本形式或詞根（稱為詞幹化），使系統更容易在不同詞形變化中匹配意義相近的單字。stemmer 篩選器支援多種語言，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 中的自訂篩選器。若要使用此功能，請在篩選器配置中指定"type": "stemmer" ，並搭配language 參數來選擇所需的詞幹化語言。

Python Java Go Rust C++ NodeJS C# cURL 
analyzer_params = {
    "tokenizer": "standard",
    "filter":[{
        "type": "stemmer", # Specifies the filter type as stemmer
        "language": "english", # Sets the language for stemming to English
    }],
}

import java.util.Collections;
import java.util.HashMap;
import java.util.Map;

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");
                }}
        )
);

analyzerParams := map[string]any{"tokenizer": "standard",
    "filter": []any{map[string]any{
        "type":     "stemmer",
        "language": "english",
    }}}

let analyzer_params = serde_json::json!({
    "tokenizer": "standard",
    "filter": [
        { "type": "stemmer", "language": "english" }
    ]
});

nlohmann::json analyzer_params = {
    {"tokenizer", "standard"},
    {"filter", {
        {
            {"type", "stemmer"},
            {"language", "english"}
        }
    }}
};

const analyzer_params = {
    "tokenizer": "standard",
    "filter":[{
        "type": "stemmer", // Specifies the filter type as stemmer
        "language": "english", // Sets the language for stemming to English
    }],
};

using System.Collections.Generic;

var analyzerParams = new Dictionary<string, object>
{
    ["tokenizer"] = "standard",
    ["filter"] = new object[]
    {
        new Dictionary<string, object> { ["type"] = "stemmer", ["language"] = "english" } // Specifies the filter type as stemmer and the language to English
    },
};

# restful
analyzerParams='{
  "tokenizer": "standard",
  "filter": [
    {
      "type": "stemmer",
      "language": "english"
    }
  ]
}'

stemmer 過濾器接受以下可配置參數。

參數說明
language指定詞幹化處理的語言。支援的語言包括："arabic" 、"danish" 、"dutch" 、"english" 、"finnish" 、"french" 、"german" 、"greek" 、"hungarian" 、"italian" 、"norwegian" 、"portuguese" 、"romanian" 、"russian" 、"spanish" 、"swedish" 、"tamil" 、"turkish"

stemmer 篩選器是針對分詞器所產生的詞項進行處理，因此必須與分詞器搭配使用。

對於阿拉伯文，在大多數情況下應使用內建的 arabic 分析器。內建分析器包含阿拉伯語詞幹化，以及阿拉伯語正規化、小數位數正規化與阿拉伯語停用詞移除功能。僅當您需要建立自訂分析器管線時，才應直接使用stemmer 篩選器。

定義analyzer_params 後，您可在定義集合架構時將其套用至VARCHAR 欄位。這使Milvus能使用指定的分析器處理該欄位中的文字，以實現高效的詞元化與過濾。詳細資訊請參閱「使用範例」。

範例

在將分析器配置套用至您的集合架構之前，請先使用 `run_analyzer ` 方法驗證其行為。

分析器設定

Python Java Go Rust C++ NodeJS C# cURL 
analyzer_params = {
    "tokenizer": "standard",
    "filter":[{
        "type": "stemmer", # Specifies the filter type as stemmer
        "language": "english", # Sets the language for stemming to English
    }],
}

import java.util.Collections;
import java.util.HashMap;
import java.util.Map;

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");
                }}
        )
);

analyzerParams := map[string]any{"tokenizer": "standard",
    "filter": []any{map[string]any{
        "type":     "stemmer",
        "language": "english",
    }}}

let analyzer_params = serde_json::json!({
    "tokenizer": "standard",
    "filter": [
        { "type": "stemmer", "language": "english" }
    ]
});

nlohmann::json analyzer_params = {
    {"tokenizer", "standard"},
    {"filter", {
        {
            {"type", "stemmer"},
            {"language", "english"}
        }
    }}
};

const analyzer_params = {
    "tokenizer": "standard",
    "filter":[{
        "type": "stemmer", // Specifies the filter type as stemmer
        "language": "english", // Sets the language for stemming to English
    }],
};

using System.Collections.Generic;

var analyzerParams = new Dictionary<string, object>
{
    ["tokenizer"] = "standard",
    ["filter"] = new object[]
    {
        new Dictionary<string, object> { ["type"] = "stemmer", ["language"] = "english" } // Specifies the filter type as stemmer and the language to English
    },
};

# restful
analyzerParams='{
  "tokenizer": "standard",
  "filter": [
    {
      "type": "stemmer",
      "language": "english"
    }
  ]
}'

使用以下方式進行驗證run_analyzer

Python Java Go Rust C++ NodeJS C# cURL 
from pymilvus import (
    MilvusClient,
)

client = MilvusClient(
    uri="http://localhost:19530",
    token="root:Milvus"
)

# 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 java.util.*;
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")
        .token("root:Milvus")
        .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();

import (
    "context"
    "fmt"

    "github.com/milvus-io/milvus/client/v3/milvusclient"
)

ctx := context.Background()

client, err := milvusclient.New(ctx, &milvusclient.ClientConfig{
    Address: "http://localhost:19530",
    APIKey:  "root:Milvus",
})
if err != nil {
    fmt.Println(err.Error())
    // handle error
}

texts := []string{"running runs looked ran runner"}
option := milvusclient.NewRunAnalyzerOption(texts...).
    WithAnalyzerParams(analyzerParams)

result, err := client.RunAnalyzer(ctx, option)
if err != nil {
    fmt.Println(err.Error())
    // handle error
}

for _, r := range result {
    for _, token := range r.Tokens {
        fmt.Println("Standard analyzer output:", token.Text)
    }
}

use milvus::v2::error::Result;
use milvus::v2::prelude::*;

let config = ConnectConfig::new().uri("http://localhost:19530").token("root:Milvus");
let client = ClientV2::new(&config).await?;

let sample_text = "running runs looked ran runner";
let result = client
    .run_analyzer(
        RunAnalyzerRequest::builder()
            .texts(vec![sample_text])
            .analyzer_params(analyzer_params)
            .build()?,
    )
    .await?;

println!("Standard analyzer output: {:?}", result);

#include "milvus/MilvusClientV2.h"
#include <iostream>
#include <string>

auto client = milvus::MilvusClientV2::Create();

milvus::ConnectParam connect_param{"http://localhost:19530", "root:Milvus"};
auto status = client->Connect(connect_param);
if (!status.IsOk()) {
    std::cout << status.Message() << std::endl;
}

std::string text = "running runs looked ran runner";
auto request = milvus::RunAnalyzerRequest()
                       .AddText(text)
                       .WithAnalyzerParams(analyzer_params);

milvus::RunAnalyzerResponse response;
status = client->RunAnalyzer(request, response);
if (!status.IsOk()) {
    std::cout << status.Message() << std::endl;
}

import { MilvusClient } from "@zilliz/milvus2-sdk-node";

const client = new MilvusClient({
    address: "http://localhost:19530",
    token: "root:Milvus",
});

// Sample text to analyze
const sample_text = "running runs looked ran runner";

// Run the standard analyzer with the defined configuration
const result = await client.runAnalyzer({
    text: sample_text,
    analyzer_params: analyzer_params
});
console.log("Standard analyzer output:", result);

using Milvus.Client.V2;
using Milvus.Client.V2.Requests.Utility;
using Milvus.Client.V2.Responses.Utility;
using Milvus.Client.V2.Types;

var client = new MilvusClientV2(new ConnectConfig
{
    Uri = "http://localhost:19530",
    ApiKey = "root:Milvus"
});
await client.ConnectAsync();

// Sample text to analyze
var sampleText = "running runs looked ran runner";

// Run the standard analyzer with the defined configuration
RunAnalyzerResp result = await client.RunAnalyzerAsync(new RunAnalyzerReq
{
    AnalyzerParams = analyzerParams,
    Texts = new[] { sampleText }
});
Console.WriteLine("Standard analyzer output: " + string.Join(", ", result.Results.SelectMany(r => r.Tokens).Select(t => t.Token)));

export CLUSTER_ENDPOINT="http://localhost:19530"
export TOKEN="root:Milvus"

curl --request POST \
--url "${CLUSTER_ENDPOINT}/v2/vectordb/common/run_analyzer" \
--header "Authorization: Bearer ${TOKEN}" \
--header "Content-Type: application/json" \
--header "Request-Timeout: 10" \
-d '{
    "text": ["running runs looked ran runner"],
    "analyzerParams": "{\"tokenizer\": \"standard\", \"filter\": [{\"type\": \"stemmer\", \"language\": \"english\"}]}"
}'

預期輸出

['run', 'run', 'look', 'ran', 'runner']

翻譯者DeepL

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