758 lines
24 KiB
Markdown
758 lines
24 KiB
Markdown
# 選項詞彙庫功能規格書
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**版本**: 1.0
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**日期**: 2025-09-29
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**專案**: DramaLing 智能英語學習系統
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**功能模組**: 測驗選項生成系統
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---
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## 📋 功能概述
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### 背景
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目前 DramaLing 系統的測驗選項生成存在以下問題：
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- **前端使用簡單佔位符**：`["其他選項1", "其他選項2", "其他選項3"]`
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- **後端隨機選擇**：從用戶自己的詞卡中隨機選取，缺乏智能性
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- **選項品質不穩定**：可能產生過於簡單或困難的干擾項
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- **缺乏科學性**：未考慮語言學習的認知負荷理論
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### 目標
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建立一個**智能選項詞彙庫系統**，根據目標詞彙的特徵自動生成高品質的測驗干擾項。
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### 核心特性
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- **三參數匹配**：CEFR 等級、字數、詞性
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- **智能篩選**：避免同義詞、相似拼寫等不合適的選項
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- **可擴展性**：支援持續新增詞彙和優化演算法
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- **效能優化**：透過索引和快取確保快速回應
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---
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## 🎯 功能需求
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### 核心需求
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| 需求ID | 描述 | 優先級 |
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|--------|------|-------|
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| REQ-001 | 根據 CEFR 等級匹配相近難度的詞彙 | 高 |
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| REQ-002 | 根據字數（字元長度）匹配類似長度的詞彙 | 高 |
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| REQ-003 | 根據詞性匹配相同詞性的詞彙 | 高 |
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| REQ-004 | 每次生成 3 個不同的干擾項 | 高 |
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| REQ-005 | 避免選擇同義詞作為干擾項 | 中 |
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| REQ-006 | 避免選擇拼寫過於相似的詞彙 | 中 |
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| REQ-007 | 支援多種測驗類型（詞彙選擇、聽力等） | 中 |
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| REQ-008 | 提供詞彙庫管理介面 | 低 |
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### 非功能需求
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| 需求ID | 描述 | 指標 |
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|--------|------|-------|
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| NFR-001 | 回應時間 | < 100ms |
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| NFR-002 | 詞彙庫大小 | 初期 ≥ 10,000 詞 |
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| NFR-003 | 可用性 | 99.9% |
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| NFR-004 | 擴展性 | 支援 100,000+ 詞彙 |
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---
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## 🏗️ 系統設計
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### 整體架構
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```
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┌─────────────────┐ ┌─────────────────┐ ┌─────────────────┐
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│ 前端測驗頁面 │────│ 選項生成API │────│ 詞彙庫服務 │
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└─────────────────┘ └─────────────────┘ └─────────────────┘
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│ │
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▼ ▼
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┌─────────────────┐ ┌─────────────────┐
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│ 快取層 │ │ 選項詞彙庫 │
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│ (Redis/Memory) │ │ (Database) │
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└─────────────────┘ └─────────────────┘
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```
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### 核心元件
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1. **OptionsVocabulary 實體** - 詞彙庫資料模型
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2. **OptionsVocabularyService** - 詞彙庫業務邏輯
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3. **DistractorGenerationService** - 干擾項生成邏輯
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4. **VocabularyMatchingEngine** - 詞彙匹配演算法
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---
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## 📊 資料模型設計
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### OptionsVocabulary 實體
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```csharp
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namespace DramaLing.Api.Models.Entities;
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public class OptionsVocabulary
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{
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/// <summary>
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/// 主鍵
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/// </summary>
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public Guid Id { get; set; }
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/// <summary>
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/// 詞彙內容
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/// </summary>
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[Required]
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[MaxLength(100)]
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[Index("IX_OptionsVocabulary_Word", IsUnique = true)]
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public string Word { get; set; } = string.Empty;
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/// <summary>
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/// CEFR 難度等級 (A1, A2, B1, B2, C1, C2)
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/// </summary>
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[Required]
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[MaxLength(2)]
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[Index("IX_OptionsVocabulary_CEFR")]
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public string CEFRLevel { get; set; } = string.Empty;
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/// <summary>
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/// 詞性 (noun, verb, adjective, adverb, etc.)
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/// </summary>
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[Required]
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[MaxLength(20)]
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[Index("IX_OptionsVocabulary_PartOfSpeech")]
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public string PartOfSpeech { get; set; } = string.Empty;
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/// <summary>
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/// 字數（字元長度）
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/// </summary>
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[Index("IX_OptionsVocabulary_WordLength")]
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public int WordLength { get; set; }
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/// <summary>
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/// 詞彙使用頻率（1-5，5最高）
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/// </summary>
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[Range(1, 5)]
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public int FrequencyRating { get; set; } = 3;
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/// <summary>
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/// 中文翻譯（用於避免同義詞）
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/// </summary>
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[MaxLength(200)]
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public string? ChineseTranslation { get; set; }
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/// <summary>
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/// 同義詞列表（JSON 格式，用於排除）
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/// </summary>
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[MaxLength(500)]
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public string? Synonyms { get; set; }
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/// <summary>
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/// 詞彙來源（dictionary, corpus, manual）
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/// </summary>
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[MaxLength(50)]
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public string? Source { get; set; }
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/// <summary>
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/// 是否啟用
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/// </summary>
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public bool IsActive { get; set; } = true;
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/// <summary>
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/// 品質評分（用於優先排序）
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/// </summary>
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[Range(0, 100)]
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public int QualityScore { get; set; } = 50;
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/// <summary>
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/// 創建時間
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/// </summary>
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public DateTime CreatedAt { get; set; } = DateTime.UtcNow;
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/// <summary>
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/// 更新時間
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/// </summary>
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public DateTime UpdatedAt { get; set; } = DateTime.UtcNow;
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}
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```
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### 複合索引設計
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```csharp
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// 在 DbContext 中配置
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protected override void OnModelCreating(ModelBuilder modelBuilder)
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{
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// 核心查詢索引：CEFR + 詞性 + 字數
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modelBuilder.Entity<OptionsVocabulary>()
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.HasIndex(e => new { e.CEFRLevel, e.PartOfSpeech, e.WordLength })
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.HasDatabaseName("IX_OptionsVocabulary_Core_Matching");
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// 啟用狀態索引
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modelBuilder.Entity<OptionsVocabulary>()
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.HasIndex(e => new { e.IsActive, e.QualityScore })
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.HasDatabaseName("IX_OptionsVocabulary_Active_Quality");
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}
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```
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---
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## 🔧 服務層設計
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### IOptionsVocabularyService 介面
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```csharp
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namespace DramaLing.Api.Services;
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public interface IOptionsVocabularyService
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{
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/// <summary>
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/// 根據目標詞彙生成干擾項
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/// </summary>
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Task<List<string>> GenerateDistractorsAsync(
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string targetWord,
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string cefrLevel,
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string partOfSpeech,
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int count = 3);
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/// <summary>
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/// 新增詞彙到選項庫
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/// </summary>
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Task<bool> AddVocabularyAsync(OptionsVocabulary vocabulary);
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/// <summary>
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/// 批量匯入詞彙
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/// </summary>
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Task<int> BulkImportAsync(List<OptionsVocabulary> vocabularies);
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/// <summary>
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/// 根據條件搜尋詞彙
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/// </summary>
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Task<List<OptionsVocabulary>> SearchVocabulariesAsync(
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string? cefrLevel = null,
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string? partOfSpeech = null,
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int? minLength = null,
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int? maxLength = null,
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int limit = 100);
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}
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```
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### DistractorGenerationService 核心邏輯
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```csharp
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public class DistractorGenerationService
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{
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private readonly DramaLingDbContext _context;
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private readonly IMemoryCache _cache;
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private readonly ILogger<DistractorGenerationService> _logger;
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public async Task<List<string>> GenerateDistractorsAsync(
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string targetWord,
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string cefrLevel,
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string partOfSpeech)
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{
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var targetLength = targetWord.Length;
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// 1. 基礎篩選條件
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var baseQuery = _context.OptionsVocabularies
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.Where(v => v.IsActive && v.Word != targetWord);
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// 2. CEFR 等級匹配（相同等級 + 相鄰等級）
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var allowedCEFRLevels = GetAllowedCEFRLevels(cefrLevel);
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baseQuery = baseQuery.Where(v => allowedCEFRLevels.Contains(v.CEFRLevel));
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// 3. 詞性匹配
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baseQuery = baseQuery.Where(v => v.PartOfSpeech == partOfSpeech);
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// 4. 字數匹配（±2 字元範圍）
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var minLength = Math.Max(1, targetLength - 2);
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var maxLength = targetLength + 2;
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baseQuery = baseQuery.Where(v => v.WordLength >= minLength && v.WordLength <= maxLength);
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// 5. 排除同義詞（如果有定義）
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// TODO: 實現同義詞排除邏輯
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// 6. 按品質評分和隨機性排序
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var candidates = await baseQuery
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.OrderByDescending(v => v.QualityScore)
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.ThenBy(v => Guid.NewGuid())
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.Take(10) // 取更多候選詞再篩選
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.Select(v => v.Word)
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.ToListAsync();
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// 7. 最終篩選和回傳
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return candidates.Take(3).ToList();
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}
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private List<string> GetAllowedCEFRLevels(string targetLevel)
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{
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var levels = new[] { "A1", "A2", "B1", "B2", "C1", "C2" };
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var targetIndex = Array.IndexOf(levels, targetLevel);
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if (targetIndex == -1) return new List<string> { targetLevel };
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var allowed = new List<string> { targetLevel };
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// 加入相鄰等級
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if (targetIndex > 0) allowed.Add(levels[targetIndex - 1]);
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if (targetIndex < levels.Length - 1) allowed.Add(levels[targetIndex + 1]);
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return allowed;
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}
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}
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```
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---
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## 🌐 API 設計
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### 新增到 StudyController
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```csharp
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/// <summary>
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/// 生成測驗選項（使用詞彙庫）
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/// </summary>
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[HttpGet("question-options/{flashcardId}")]
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public async Task<ActionResult<QuestionOptionsResponse>> GenerateQuestionOptions(
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Guid flashcardId,
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[FromQuery] string questionType = "vocab-choice")
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{
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try
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{
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var flashcard = await _context.Flashcards.FindAsync(flashcardId);
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if (flashcard == null)
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return NotFound(new { Error = "Flashcard not found" });
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var options = await _distractorGenerationService.GenerateDistractorsAsync(
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flashcard.Word,
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flashcard.DifficultyLevel ?? "B1",
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flashcard.PartOfSpeech ?? "noun");
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// 加入正確答案並隨機打亂
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var allOptions = new List<string> { flashcard.Word };
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allOptions.AddRange(options);
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var shuffledOptions = allOptions.OrderBy(x => Guid.NewGuid()).ToArray();
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return Ok(new QuestionOptionsResponse
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{
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QuestionType = questionType,
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Options = shuffledOptions,
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CorrectAnswer = flashcard.Word,
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TargetWord = flashcard.Word,
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CEFRLevel = flashcard.DifficultyLevel,
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PartOfSpeech = flashcard.PartOfSpeech
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});
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}
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catch (Exception ex)
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{
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_logger.LogError(ex, "Error generating question options for flashcard {FlashcardId}", flashcardId);
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return StatusCode(500, new { Error = "Internal server error" });
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}
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}
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```
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### 詞彙庫管理 API
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```csharp
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/// <summary>
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/// 詞彙庫管理控制器
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/// </summary>
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[ApiController]
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[Route("api/[controller]")]
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[Authorize(Roles = "Admin")]
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public class OptionsVocabularyController : ControllerBase
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{
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private readonly IOptionsVocabularyService _vocabularyService;
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/// <summary>
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/// 新增詞彙到選項庫
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/// </summary>
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[HttpPost]
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public async Task<ActionResult> AddVocabulary([FromBody] AddVocabularyRequest request)
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{
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var vocabulary = new OptionsVocabulary
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{
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Word = request.Word,
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CEFRLevel = request.CEFRLevel,
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PartOfSpeech = request.PartOfSpeech,
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WordLength = request.Word.Length,
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FrequencyRating = request.FrequencyRating,
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ChineseTranslation = request.ChineseTranslation,
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Source = "manual"
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};
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var success = await _vocabularyService.AddVocabularyAsync(vocabulary);
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return success ? Ok() : BadRequest();
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}
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/// <summary>
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/// 批量匯入詞彙
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/// </summary>
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[HttpPost("bulk-import")]
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public async Task<ActionResult> BulkImport([FromBody] List<AddVocabularyRequest> requests)
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{
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var vocabularies = requests.Select(r => new OptionsVocabulary
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{
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Word = r.Word,
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CEFRLevel = r.CEFRLevel,
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PartOfSpeech = r.PartOfSpeech,
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WordLength = r.Word.Length,
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FrequencyRating = r.FrequencyRating,
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ChineseTranslation = r.ChineseTranslation,
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Source = "bulk-import"
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}).ToList();
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var importedCount = await _vocabularyService.BulkImportAsync(vocabularies);
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return Ok(new { ImportedCount = importedCount });
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}
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/// <summary>
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/// 搜尋詞彙庫
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/// </summary>
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[HttpGet("search")]
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public async Task<ActionResult<List<OptionsVocabulary>>> SearchVocabularies(
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[FromQuery] string? cefrLevel = null,
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[FromQuery] string? partOfSpeech = null,
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[FromQuery] int? minLength = null,
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[FromQuery] int? maxLength = null,
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[FromQuery] int limit = 100)
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{
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var vocabularies = await _vocabularyService.SearchVocabulariesAsync(
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cefrLevel, partOfSpeech, minLength, maxLength, limit);
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return Ok(vocabularies);
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}
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}
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```
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---
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## 📁 DTOs 定義
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### QuestionOptionsResponse
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```csharp
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namespace DramaLing.Api.Models.DTOs;
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public class QuestionOptionsResponse
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{
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public string QuestionType { get; set; } = string.Empty;
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public string[] Options { get; set; } = Array.Empty<string>();
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public string CorrectAnswer { get; set; } = string.Empty;
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public string TargetWord { get; set; } = string.Empty;
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public string? CEFRLevel { get; set; }
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public string? PartOfSpeech { get; set; }
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public DateTime GeneratedAt { get; set; } = DateTime.UtcNow;
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}
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```
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### AddVocabularyRequest
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```csharp
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public class AddVocabularyRequest
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{
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[Required]
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[MaxLength(100)]
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public string Word { get; set; } = string.Empty;
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[Required]
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[RegularExpression("^(A1|A2|B1|B2|C1|C2)$")]
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public string CEFRLevel { get; set; } = string.Empty;
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[Required]
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[MaxLength(20)]
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public string PartOfSpeech { get; set; } = string.Empty;
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[Range(1, 5)]
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public int FrequencyRating { get; set; } = 3;
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[MaxLength(200)]
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public string? ChineseTranslation { get; set; }
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[MaxLength(500)]
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public string? Synonyms { get; set; }
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}
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```
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---
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## 💾 資料庫遷移
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### Migration 檔案
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```csharp
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public partial class AddOptionsVocabularyTable : Migration
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{
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protected override void Up(MigrationBuilder migrationBuilder)
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{
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migrationBuilder.CreateTable(
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name: "OptionsVocabularies",
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columns: table => new
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{
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Id = table.Column<Guid>(nullable: false),
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Word = table.Column<string>(maxLength: 100, nullable: false),
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CEFRLevel = table.Column<string>(maxLength: 2, nullable: false),
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PartOfSpeech = table.Column<string>(maxLength: 20, nullable: false),
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WordLength = table.Column<int>(nullable: false),
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FrequencyRating = table.Column<int>(nullable: false, defaultValue: 3),
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ChineseTranslation = table.Column<string>(maxLength: 200, nullable: true),
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Synonyms = table.Column<string>(maxLength: 500, nullable: true),
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Source = table.Column<string>(maxLength: 50, nullable: true),
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IsActive = table.Column<bool>(nullable: false, defaultValue: true),
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QualityScore = table.Column<int>(nullable: false, defaultValue: 50),
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CreatedAt = table.Column<DateTime>(nullable: false),
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UpdatedAt = table.Column<DateTime>(nullable: false)
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},
|
||
constraints: table =>
|
||
{
|
||
table.PrimaryKey("PK_OptionsVocabularies", x => x.Id);
|
||
});
|
||
|
||
// 索引
|
||
migrationBuilder.CreateIndex(
|
||
name: "IX_OptionsVocabulary_Word",
|
||
table: "OptionsVocabularies",
|
||
column: "Word",
|
||
unique: true);
|
||
|
||
migrationBuilder.CreateIndex(
|
||
name: "IX_OptionsVocabulary_Core_Matching",
|
||
table: "OptionsVocabularies",
|
||
columns: new[] { "CEFRLevel", "PartOfSpeech", "WordLength" });
|
||
|
||
migrationBuilder.CreateIndex(
|
||
name: "IX_OptionsVocabulary_Active_Quality",
|
||
table: "OptionsVocabularies",
|
||
columns: new[] { "IsActive", "QualityScore" });
|
||
}
|
||
|
||
protected override void Down(MigrationBuilder migrationBuilder)
|
||
{
|
||
migrationBuilder.DropTable(name: "OptionsVocabularies");
|
||
}
|
||
}
|
||
```
|
||
|
||
---
|
||
|
||
## 🔄 使用案例
|
||
|
||
### 案例 1：詞彙選擇題
|
||
```
|
||
目標詞彙: "beautiful" (B1, adjective, 9字元)
|
||
|
||
篩選條件:
|
||
- CEFR: A2, B1, B2 (相鄰等級)
|
||
- 詞性: adjective
|
||
- 字數: 7-11 字元
|
||
|
||
可能的干擾項:
|
||
- "wonderful" (B1, adjective, 9字元)
|
||
- "excellent" (B2, adjective, 9字元)
|
||
- "attractive" (B2, adjective, 10字元)
|
||
|
||
最終選項: ["beautiful", "wonderful", "excellent", "attractive"]
|
||
```
|
||
|
||
### 案例 2：聽力測驗
|
||
```
|
||
目標詞彙: "running" (A2, verb, 7字元)
|
||
|
||
篩選條件:
|
||
- CEFR: A1, A2, B1
|
||
- 詞性: verb
|
||
- 字數: 5-9 字元
|
||
|
||
可能的干擾項:
|
||
- "jumping" (A2, verb, 7字元)
|
||
- "walking" (A1, verb, 7字元)
|
||
- "playing" (A2, verb, 7字元)
|
||
|
||
最終選項: ["running", "jumping", "walking", "playing"]
|
||
```
|
||
|
||
---
|
||
|
||
## ⚡ 效能考量
|
||
|
||
### 查詢優化
|
||
1. **複合索引**：(CEFRLevel, PartOfSpeech, WordLength)
|
||
2. **覆蓋索引**：包含常用查詢欄位
|
||
3. **分頁查詢**：避免一次載入過多資料
|
||
|
||
### 快取策略
|
||
```csharp
|
||
public class CachedDistractorGenerationService
|
||
{
|
||
private readonly IMemoryCache _cache;
|
||
private readonly TimeSpan _cacheExpiry = TimeSpan.FromHours(1);
|
||
|
||
public async Task<List<string>> GenerateDistractorsAsync(string targetWord, string cefrLevel, string partOfSpeech)
|
||
{
|
||
var cacheKey = $"distractors:{targetWord}:{cefrLevel}:{partOfSpeech}";
|
||
|
||
if (_cache.TryGetValue(cacheKey, out List<string> cachedResult))
|
||
{
|
||
return cachedResult;
|
||
}
|
||
|
||
var result = await GenerateDistractorsInternalAsync(targetWord, cefrLevel, partOfSpeech);
|
||
|
||
_cache.Set(cacheKey, result, _cacheExpiry);
|
||
return result;
|
||
}
|
||
}
|
||
```
|
||
|
||
### 效能指標
|
||
| 指標 | 目標值 | 監控方式 |
|
||
|------|--------|----------|
|
||
| API 回應時間 | < 100ms | Application Insights |
|
||
| 資料庫查詢時間 | < 50ms | EF Core 日誌 |
|
||
| 快取命中率 | > 80% | 自訂計數器 |
|
||
| 併發請求數 | > 1000 req/s | 負載測試 |
|
||
|
||
---
|
||
|
||
## 📊 初始資料建立
|
||
|
||
### 資料來源建議
|
||
1. **CEFR 詞彙表**
|
||
- Cambridge English Vocabulary Profile
|
||
- Oxford 3000/5000 詞彙表
|
||
- 各級別教材詞彙表
|
||
|
||
2. **詞性標注**
|
||
- WordNet 資料庫
|
||
- 英語詞性詞典
|
||
- 語料庫分析結果
|
||
|
||
3. **頻率評級**
|
||
- Google Ngram Corpus
|
||
- Brown Corpus
|
||
- 現代英語使用頻率統計
|
||
|
||
### 初始資料腳本
|
||
```csharp
|
||
public class VocabularySeeder
|
||
{
|
||
public async Task SeedInitialVocabularyAsync()
|
||
{
|
||
var vocabularies = new List<OptionsVocabulary>
|
||
{
|
||
// A1 Level - 名詞
|
||
new() { Word = "cat", CEFRLevel = "A1", PartOfSpeech = "noun", WordLength = 3, FrequencyRating = 5, ChineseTranslation = "貓" },
|
||
new() { Word = "dog", CEFRLevel = "A1", PartOfSpeech = "noun", WordLength = 3, FrequencyRating = 5, ChineseTranslation = "狗" },
|
||
new() { Word = "book", CEFRLevel = "A1", PartOfSpeech = "noun", WordLength = 4, FrequencyRating = 5, ChineseTranslation = "書" },
|
||
|
||
// A1 Level - 動詞
|
||
new() { Word = "eat", CEFRLevel = "A1", PartOfSpeech = "verb", WordLength = 3, FrequencyRating = 5, ChineseTranslation = "吃" },
|
||
new() { Word = "run", CEFRLevel = "A1", PartOfSpeech = "verb", WordLength = 3, FrequencyRating = 4, ChineseTranslation = "跑" },
|
||
new() { Word = "walk", CEFRLevel = "A1", PartOfSpeech = "verb", WordLength = 4, FrequencyRating = 5, ChineseTranslation = "走" },
|
||
|
||
// B1 Level - 形容詞
|
||
new() { Word = "beautiful", CEFRLevel = "B1", PartOfSpeech = "adjective", WordLength = 9, FrequencyRating = 4, ChineseTranslation = "美麗的" },
|
||
new() { Word = "wonderful", CEFRLevel = "B1", PartOfSpeech = "adjective", WordLength = 9, FrequencyRating = 4, ChineseTranslation = "精彩的" },
|
||
new() { Word = "excellent", CEFRLevel = "B2", PartOfSpeech = "adjective", WordLength = 9, FrequencyRating = 4, ChineseTranslation = "優秀的" },
|
||
|
||
// ... 更多詞彙
|
||
};
|
||
|
||
await _context.OptionsVocabularies.AddRangeAsync(vocabularies);
|
||
await _context.SaveChangesAsync();
|
||
}
|
||
}
|
||
```
|
||
|
||
---
|
||
|
||
## 🔄 服務註冊
|
||
|
||
### Startup.cs / Program.cs
|
||
```csharp
|
||
// 註冊服務
|
||
builder.Services.AddScoped<IOptionsVocabularyService, OptionsVocabularyService>();
|
||
builder.Services.AddScoped<DistractorGenerationService>();
|
||
|
||
// 記憶體快取
|
||
builder.Services.AddMemoryCache();
|
||
|
||
// 背景服務（可選）
|
||
builder.Services.AddHostedService<VocabularyQualityScoreUpdateService>();
|
||
```
|
||
|
||
---
|
||
|
||
## 📈 品質保證
|
||
|
||
### 演算法驗證
|
||
1. **A/B 測試**：比較新舊選項生成方式的學習效果
|
||
2. **專家評審**：語言學習專家評估選項品質
|
||
3. **用戶回饋**：收集學習者對選項難度的反饋
|
||
|
||
### 監控指標
|
||
```csharp
|
||
public class DistractorQualityMetrics
|
||
{
|
||
public double AverageResponseTime { get; set; }
|
||
public double OptionVariability { get; set; } // 選項多樣性
|
||
public double CEFRLevelAccuracy { get; set; } // CEFR 匹配準確度
|
||
public double UserSatisfactionScore { get; set; } // 用戶滿意度
|
||
public int TotalDistractorsGenerated { get; set; }
|
||
public DateTime MeasuredAt { get; set; }
|
||
}
|
||
```
|
||
|
||
---
|
||
|
||
## 🚀 實作階段規劃
|
||
|
||
### Phase 1: 基礎實作 (1-2 週)
|
||
- [ ] 建立 OptionsVocabulary 實體和資料庫遷移
|
||
- [ ] 實作 OptionsVocabularyService 基礎功能
|
||
- [ ] 建立核心 API 端點
|
||
- [ ] 匯入初始詞彙資料（1000-5000 詞）
|
||
|
||
### Phase 2: 演算法優化 (1 週)
|
||
- [ ] 實作 DistractorGenerationService
|
||
- [ ] 新增同義詞排除邏輯
|
||
- [ ] 實作品質評分系統
|
||
- [ ] 加入快取機制
|
||
|
||
### Phase 3: 前端整合 (3-5 天)
|
||
- [ ] 修改前端 generateOptions 函數
|
||
- [ ] 整合新的 API 端點
|
||
- [ ] 測試各種測驗類型
|
||
- [ ] 效能測試和優化
|
||
|
||
### Phase 4: 進階功能 (1-2 週)
|
||
- [ ] 管理介面開發
|
||
- [ ] 批量匯入工具
|
||
- [ ] 監控和分析儀表板
|
||
- [ ] A/B 測試框架
|
||
|
||
---
|
||
|
||
## 📋 驗收標準
|
||
|
||
### 功能驗收
|
||
- [ ] 能根據 CEFR、詞性、字數生成合適的干擾項
|
||
- [ ] API 回應時間 < 100ms
|
||
- [ ] 生成的選項無重複
|
||
- [ ] 支援各種測驗類型
|
||
|
||
### 品質驗收
|
||
- [ ] 干擾項難度適中（不會太簡單或太困難）
|
||
- [ ] 無明顯的同義詞作為干擾項
|
||
- [ ] 拼寫差異合理（避免過於相似）
|
||
|
||
### 技術驗收
|
||
- [ ] 程式碼覆蓋率 > 80%
|
||
- [ ] 通過所有單元測試
|
||
- [ ] API 文檔完整
|
||
- [ ] 效能測試通過
|
||
|
||
---
|
||
|
||
## 🔒 安全性考量
|
||
|
||
### 資料保護
|
||
- 詞彙庫資料非敏感性，無特殊加密需求
|
||
- 管理 API 需要管理員權限驗證
|
||
- 防止 SQL 注入攻擊
|
||
|
||
### API 安全
|
||
- 實作 Rate Limiting 防止濫用
|
||
- 輸入驗證和清理
|
||
- 錯誤訊息不洩露系統資訊
|
||
|
||
---
|
||
|
||
## 📚 相關文件
|
||
|
||
- [智能複習系統-第五階段開發計劃.md](./智能複習系統-第五階段開發計劃.md)
|
||
- [後端完成度評估報告.md](./後端完成度評估報告.md)
|
||
- [DramaLing API 文檔](./docs/api-documentation.md)
|
||
|
||
---
|
||
|
||
**規格書完成日期**: 2025-09-29
|
||
**下次更新時間**: 實作完成後 |