@aiquants/fuzzy-search/dist/worker/indexWorker.mjs.map

Advanced fuzzy search library with Levenshtein distance, n-gram indexing, and Web Worker support

{"version":3,"sources":["../../src/types/index.ts","../../src/worker/common.ts","../../src/worker/indexWorker.ts"],"sourcesContent":["/**\n * @module types/index\n * @description Core types for the fuzzy search library.\n * @description あいまい検索ライブラリのコア型定義。\n */\n\n// ===== Basic Configuration Types =====\n\n/**\n * @interface FuzzySearchOptions\n * @description Configuration options for fuzzy search functionality.\n * @description あいまい検索機能の設定オプション。\n */\nexport interface FuzzySearchOptions {\n    /**\n     * @property {number} threshold - Similarity threshold (0.0-1.0).\n     * @description 類似度の閾値。この値以上のスコアを持つアイテムが結果に含まれます。\n     */\n    threshold: number\n\n    /**\n     * @property {boolean} caseSensitive - Whether to perform case-sensitive search.\n     * @description 大文字小文字を区別するかどうか。true の場合、区別して検索します。\n     */\n    caseSensitive: boolean\n\n    /**\n     * @property {number} learningWeight - Learning weight for user behavior (0.0-2.0).\n     * @description ユーザーの選択行動に基づく学習による重み付け。1.0より大きいと学習効果が強まります。\n     */\n    learningWeight: number\n\n    /**\n     * @property {number} debounceMs - Debounce time in milliseconds.\n     * @description 検索入力のデバウンス時間（ミリ秒）。連続入力時の不要な検索処理を防ぎます。\n     */\n    debounceMs: number\n\n    /**\n     * @property {'and' | 'or'} multiTermOperator - Logical operator applied to space-separated query terms.\n     * @description スペース区切りのクエリ語に適用する論理演算子。\n     */\n    multiTermOperator: \"and\" | \"or\"\n\n    /**\n     * @property {boolean} autoSearchOnIndexRebuild - Whether to trigger a search immediately after the index is rebuilt.\n     * @description インデックス再構築直後に自動的に検索を実行するかどうか。\n     */\n    autoSearchOnIndexRebuild: boolean\n\n    /**\n     * @property {Record<string, number>} customWeights - Custom field weights for scoring.\n     * @description 特定のフィールドに対するカスタムの重み設定。スコアリングに影響します。\n     */\n    customWeights: Record<string, number>\n\n    /**\n     * @property {number} ngramSize - N-gram size for indexing (default: 2).\n     * @description インデックス作成に使用する N-gram のサイズ。通常は2または3が使われます。\n     */\n    ngramSize: number\n\n    /**\n     * @property {number} minNgramOverlap - Minimum n-gram overlap for candidate filtering.\n     * @description 候補フィルタリングのための最小 N-gram 重複数。\n     */\n    minNgramOverlap: number\n\n    /**\n     * @property {'score' | 'relevance' | 'original'} sortBy - Sort results by field.\n     * @description 検索結果のソート基準。'score' (類似度スコア)、'relevance' (関連性)、'original' (元の順序) から選択します。\n     */\n    sortBy: \"score\" | \"relevance\" | \"original\"\n\n    /**\n     * @property {'asc' | 'desc'} sortOrder - Sort order (ascending or descending).\n     * @description ソート順序 (昇順または降順)。\n     */\n    sortOrder: \"asc\" | \"desc\"\n\n    /**\n     * @property {boolean} enableIndexFiltering - Enable index-based filtering stage.\n     * @description インデックスベースのフィルタリングステージを有効にするかどうか。\n     */\n    enableIndexFiltering: boolean\n\n    /**\n     * @property {boolean} enableLevenshtein - Enable Levenshtein distance calculation stage.\n     * @description レーベンシュタイン距離計算ステージを有効にするかどうか。\n     */\n    enableLevenshtein: boolean\n\n    /**\n     * @property {'index-first' | 'levenshtein-first' | 'balanced'} parallelSearchStrategy - Parallel search strategy.\n     * @description 並列検索の戦略。'index-first' (インデックス優先)、'levenshtein-first' (レーベンシュタイン優先)、'balanced' (バランス) から選択します。\n     */\n    parallelSearchStrategy: \"index-first\" | \"levenshtein-first\" | \"balanced\"\n\n    /**\n     * @property {object} [workerUrls] - Custom Worker URLs for external hosting.\n     * @description 外部ホスティング用のカスタム Worker URL。\n     */\n    workerUrls?: {\n        /**\n         * @property {string} [indexWorker] - URL for the index worker.\n         * @description Index Worker の URL。\n         */\n        indexWorker?: string\n        /**\n         * @property {string} [levenshteinWorker] - URL for the levenshtein worker.\n         * @description Levenshtein Worker の URL。\n         */\n        levenshteinWorker?: string\n    }\n\n    /**\n     * @property {object} [indexWorkerOptions] - Index Worker specific parameters.\n     * @description Index Worker 固有のパラメータ。\n     */\n    indexWorkerOptions?: {\n        /**\n         * @property {IndexStrategy} [strategy] - Index Worker search strategy ('fast' | 'accurate' | 'hybrid').\n         * @description Index Worker の検索戦略。\n         */\n        strategy?: IndexStrategy\n        /**\n         * @property {number} [threshold] - Similarity threshold for Index Worker (0.0-1.0).\n         * @description Index Worker 用の類似度閾値。\n         */\n        threshold?: number\n        /**\n         * @property {number} [ngramOverlapThreshold] - N-gram overlap threshold ratio (0.0-1.0).\n         * @description N-gram 重複閾値の比率。\n         */\n        ngramOverlapThreshold?: number\n        /**\n         * @property {number} [minCandidatesRatio] - Minimum candidates ratio for fast search (0.0-1.0).\n         * @description 高速検索用の最小候補比率。\n         */\n        minCandidatesRatio?: number\n        /**\n         * @property {number} [maxCandidatesRatio] - Maximum candidates ratio to trigger filtering (0.0-1.0).\n         * @description フィルタリングを発動するための最大候補比率。\n         */\n        maxCandidatesRatio?: number\n        /**\n         * @property {number} [jaroWinklerPrefix] - Jaro-Winkler prefix scaling factor (0.0-0.25).\n         * @description Jaro-Winkler アルゴリズムの接頭辞スケーリング係数。\n         */\n        jaroWinklerPrefix?: number\n        /**\n         * @property {number} [maxResults] - Maximum number of results for Index Worker.\n         * @description Index Worker 用の最大結果数。\n         */\n        maxResults?: number\n        /**\n         * @property {number} [relevanceFieldWeight] - Weight for matched field count in relevance score (0.0-1.0).\n         * @description relevance スコア計算時のマッチフィールド数の重み。\n         */\n        relevanceFieldWeight?: number\n        /**\n         * @property {number} [relevancePerfectMatchBonus] - Bonus for perfect match in relevance score (0.0-1.0).\n         * @description relevance スコア計算時の完全一致ボーナス。\n         */\n        relevancePerfectMatchBonus?: number\n    }\n\n    /**\n     * @property {object} [levenshteinWorkerOptions] - Levenshtein Worker specific parameters.\n     * @description Levenshtein Worker 固有のパラメータ。\n     */\n    levenshteinWorkerOptions?: {\n        /**\n         * @property {number} [threshold] - Similarity threshold for Levenshtein Worker (0.0-1.0).\n         * @description Levenshtein Worker 用の類似度閾値。\n         */\n        threshold?: number\n        /**\n         * @property {number} [lengthSimilarityThreshold] - Length-based similarity threshold for early rejection.\n         * @description 長さベースの類似度閾値（早期リジェクション用）。\n         */\n        lengthSimilarityThreshold?: number\n        /**\n         * @property {number} [partialMatchBonus] - Partial match bonus score.\n         * @description 部分一致が検出された場合に加算されるボーナススコア。\n         */\n        partialMatchBonus?: number\n        /**\n         * @property {number} [lengthDiffPenalty] - Length difference penalty ratio.\n         * @description 文字列長の差によるペナルティの比率。\n         */\n        lengthDiffPenalty?: number\n        /**\n         * @property {number} [maxResults] - Maximum number of results for Levenshtein Worker.\n         * @description Levenshtein Worker 用の最大結果数。\n         */\n        maxResults?: number\n        /**\n         * @property {number} [relevanceFieldWeight] - Weight for matched field count in relevance score (0.0-1.0).\n         * @description relevance スコア計算時のマッチフィールド数の重み。\n         */\n        relevanceFieldWeight?: number\n    }\n}\n\n/**\n * @type PartialFuzzySearchOptions\n * @description Partial options for initializing fuzzy search. Allows overriding a subset of the default options.\n * @description あいまい検索初期化用の部分オプション。デフォルトオプションの一部を上書きできます。\n */\nexport type PartialFuzzySearchOptions = Partial<FuzzySearchOptions>\n\n/**\n * @const DEFAULT_FUZZY_SEARCH_OPTIONS\n * @description Default options for fuzzy search. Used when no options are provided.\n * @description あいまい検索のデフォルトオプション。オプションが指定されなかった場合に使用されます。\n */\nexport const DEFAULT_FUZZY_SEARCH_OPTIONS: FuzzySearchOptions = {\n    threshold: 0.4,\n    caseSensitive: false,\n    learningWeight: 1.2,\n    debounceMs: 300,\n    multiTermOperator: \"and\",\n    autoSearchOnIndexRebuild: true,\n    customWeights: {},\n    ngramSize: 2,\n    minNgramOverlap: 1,\n    sortBy: \"relevance\",\n    sortOrder: \"desc\",\n    enableIndexFiltering: true,\n    enableLevenshtein: true,\n    parallelSearchStrategy: \"balanced\",\n    indexWorkerOptions: {\n        strategy: \"hybrid\",\n        threshold: 0.4,\n        ngramOverlapThreshold: 0.3,\n        minCandidatesRatio: 0.1,\n        maxCandidatesRatio: 0.5,\n        jaroWinklerPrefix: 0.1,\n        maxResults: 1000,\n        relevanceFieldWeight: 0.2,\n        relevancePerfectMatchBonus: 0.1,\n    },\n    levenshteinWorkerOptions: {\n        threshold: 0.3,\n        lengthSimilarityThreshold: 0.1,\n        partialMatchBonus: 0.1,\n        lengthDiffPenalty: 1.0,\n        maxResults: 1000,\n        relevanceFieldWeight: 0.15,\n    },\n}\n\n// ===== Search Result Types =====\n\n/**\n * @interface SearchResultItem\n * @description Represents an individual search result item with metadata.\n * @description メタデータを含む個別の検索結果アイテムを表します。\n * @template T - The type of the original item.\n */\nexport interface SearchResultItem<T = unknown> {\n    /**\n     * @property {T} item - The original item from the search dataset.\n     * @description 検索データセットの元のアイテム。\n     */\n    item: T\n\n    /**\n     * @property {number} score - Final similarity score (0.0-1.0+). May exceed 1.0 in Relevance mode due to bonuses.\n     * @description 最終的な類似度スコア (0.0-1.0+)。Relevance モードではボーナスにより 1.0 を超える場合があります。\n     */\n    score: number\n\n    /**\n     * @property {number} baseScore - Base similarity score before any adjustments (0.0-1.0).\n     * @description 調整前の基本類似度スコア (0.0-1.0)。Relevance モードの重み付け前の値です。\n     */\n    baseScore: number\n\n    /**\n     * @property {string[]} matchedFields - Fields that matched the search query.\n     * @description 検索クエリにマッチしたフィールドのリスト。\n     */\n    matchedFields: string[]\n\n    /**\n     * @property {number} [originalIndex] - Original index in the source dataset.\n     * @description 元のデータセットにおけるインデックス。\n     */\n    originalIndex?: number\n\n    /**\n     * @property {Record<string, unknown>} [metadata] - Additional metadata for the result.\n     * @description 結果に関連する追加のメタデータ。\n     */\n    metadata?: Record<string, unknown>\n}\n\n/**\n * @interface SearchResults\n * @description Represents the complete search results, including items and metadata.\n * @description アイテムとメタデータを含む完全な検索結果を表します。\n * @template T - The type of the items in the results.\n */\nexport interface SearchResults<T = unknown> {\n    /**\n     * @property {SearchResultItem<T>[]} results - Array of search result items.\n     * @description 検索結果アイテムの配列。\n     */\n    results: SearchResultItem<T>[]\n\n    /**\n     * @property {number} totalItems - Total number of items searched.\n     * @description 検索対象となった総アイテム数。\n     */\n    totalItems: number\n\n    /**\n     * @property {number} processingTime - Time taken for the search operation (ms).\n     * @description 検索処理全体にかかった時間（ミリ秒）。\n     */\n    processingTime: number\n\n    /**\n     * @property {string} query - The search query that was used.\n     * @description この検索で使用された検索クエリ。\n     */\n    query: string\n\n    /**\n     * @property {Partial<FuzzySearchOptions>} [options] - Search options used for this search.\n     * @description この検索で使用された検索オプション。\n     */\n    options?: Partial<FuzzySearchOptions>\n\n    /**\n     * @property {SearchStats} [stats] - Additional search statistics.\n     * @description 追加の検索統計情報。\n     */\n    stats?: SearchStats\n}\n\n// ===== Index and Strategy Types =====\n\n/**\n * @type IndexStrategy\n * @description Enumeration of available index strategies.\n * @description 利用可能なインデックス戦略の列挙。\n * - `fast`: N-gram index only for quick filtering. 高速なフィルタリングのためのN-gramインデックスのみ。\n * - `accurate`: Word-based and phonetic indexes for higher accuracy. 高精度な単語ベースおよび音韻インデックス。\n * - `hybrid`: A combination of fast and accurate strategies. 高速戦略と高精度戦略の組み合わせ。\n */\nexport type IndexStrategy = \"fast\" | \"accurate\" | \"hybrid\"\n\n/**\n * @interface IndexMetadata\n * @description Interface for metadata about the search index.\n * @description 検索インデックスに関するメタデータのインターフェース。\n */\nexport interface IndexMetadata {\n    /**\n     * @property {number} itemCount - Number of items indexed.\n     * @description インデックス化されたアイテムの総数。\n     */\n    itemCount: number\n\n    /**\n     * @property {number} buildTime - Time taken to build the index (ms).\n     * @description インデックスの構築にかかった時間（ミリ秒）。\n     */\n    buildTime: number\n\n    /**\n     * @property {number} createdAt - Index creation timestamp.\n     * @description インデックスが作成されたときのタイムスタンプ。\n     */\n    createdAt: number\n\n    /**\n     * @property {string[]} indexedFields - Fields that were indexed.\n     * @description インデックス化の対象となったフィールドのリスト。\n     */\n    indexedFields: string[]\n\n    /**\n     * @property {number} ngramSize - N-gram size used for indexing.\n     * @description インデックス化に使用された N-gram のサイズ。\n     */\n    ngramSize: number\n\n    /**\n     * @property {IndexStrategy} [strategy] - Strategy used for indexing.\n     * @description インデックス化に使用された戦略。\n     */\n    strategy?: IndexStrategy\n\n    /**\n     * @property {number} [totalIndexSize] - Total size of the index.\n     * @description インデックス全体の合計サイズ。\n     */\n    totalIndexSize?: number\n\n    /**\n     * @property {object} [indexSizes] - Individual index sizes.\n     * @description 各インデックスタイプ（ngram, word, phonetic）の個別サイズ。\n     */\n    indexSizes?: {\n        ngram: number\n        word: number\n        phonetic: number\n    }\n}\n\n// ===== Parallel Search Types =====\n\n/**\n * @type ParallelSearchStrategy\n * @description Options for parallel search strategy.\n * @description 並列検索戦略のオプション。\n *\n * @x-type-gen-skip-doc\n */\nexport type ParallelSearchStrategy = \"index-first\" | \"levenshtein-first\" | \"balanced\"\n\n/**\n * @interface ParallelSearchStageResult\n * @description Represents the result from a single stage in the parallel search pipeline.\n * @description 並列検索パイプラインの単一ステージからの結果を表します。\n * @template T - The type of the items in the results.\n */\nexport interface ParallelSearchStageResult<T = unknown> {\n    /**\n     * @property {'index' | 'levenshtein'} stage - Stage identifier.\n     * @description ステージの識別子 ('index' または 'levenshtein')。\n     */\n    stage: \"index\" | \"levenshtein\"\n\n    /**\n     * @property {SearchResultItem<T>[]} results - Search results from this stage.\n     * @description このステージからの検索結果。\n     */\n    results: SearchResultItem<T>[]\n\n    /**\n     * @property {number} processingTime - Processing time for this stage.\n     * @description このステージの処理時間。\n     */\n    processingTime: number\n\n    /**\n     * @property {number} confidence - Confidence score for the results of this stage.\n     * @description このステージの結果に対する信頼度スコア。\n     */\n    confidence: number\n\n    /**\n     * @property {number} candidatesProcessed - Number of candidates processed in this stage.\n     * @description このステージで処理された候補数。\n     */\n    candidatesProcessed: number\n}\n\n/**\n * @interface MergedParallelSearchResult\n * @description Represents the merged result from the parallel search pipeline.\n * @description 並列検索パイプラインからマージされた結果を表します。\n * @template T - The type of the items in the results.\n */\nexport interface MergedParallelSearchResult<T = unknown> {\n    /**\n     * @property {SearchResultItem<T>[]} results - Final merged search results.\n     * @description 最終的にマージされた検索結果。\n     */\n    results: SearchResultItem<T>[]\n\n    /**\n     * @property {ParallelSearchStageResult<T>} indexStage - Results from the index stage.\n     * @description インデックスステージからの結果。\n     */\n    indexStage: ParallelSearchStageResult<T>\n\n    /**\n     * @property {ParallelSearchStageResult<T>} levenshteinStage - Results from the Levenshtein stage.\n     * @description レーベンシュタインステージからの結果。\n     */\n    levenshteinStage: ParallelSearchStageResult<T>\n\n    /**\n     * @property {number} totalProcessingTime - Total processing time for the entire pipeline.\n     * @description パイプライン全体の総処理時間。\n     */\n    totalProcessingTime: number\n\n    /**\n     * @property {ParallelSearchStrategy} mergeStrategy - Merge strategy used.\n     * @description 使用されたマージ戦略。\n     */\n    mergeStrategy: ParallelSearchStrategy\n\n    /**\n     * @property {number} mergeQuality - Quality score of the merged results.\n     * @description マージされた結果の品質スコア。\n     */\n    mergeQuality: number\n}\n\n// ===== Worker Communication Types =====\n\n/**\n * @interface IndexWorkerRequest\n * @description Defines the request structure for communication with the Indexing Worker.\n * @description インデックス作成 Worker との通信のためのリクエスト構造を定義します。\n * @template T - The type of items to be indexed or searched.\n */\nexport interface IndexWorkerRequest<T = unknown> {\n    type: \"ping\" | \"buildIndex\" | \"indexSearch\" | \"getStats\" | \"resetStats\"\n    id: string\n    query?: string\n    items?: T[]\n    searchFields?: string[]\n    options?: Partial<FuzzySearchOptions>\n}\n\n/**\n * @interface UnifiedWorkerResponse\n * @description Completely unified response structure for all worker types.\n * @description すべてのワーカータイプに対応する完全統一レスポンス構造。\n * @template T - The type of items in the search results.\n */\nexport interface UnifiedWorkerResponse<T = unknown> {\n    type: string\n    id: string\n\n    // 必須フィールド\n    stats: UnifiedWorkerStats\n    metrics: WorkerPerformanceMetrics\n    processingTime: number\n\n    // 条件付きフィールド\n    results?: SearchResultItem<T>[]\n    error?: string\n\n    // ワーカー固有情報\n    workerType: \"index\" | \"levenshtein\"\n    operationMeta?: Record<string, unknown>\n}\n\n/**\n * @interface LevenshteinWorkerRequest\n * @description Defines the request structure for communication with the Levenshtein Distance Worker.\n * @description Levenshtein 距離計算 Worker との通信のためのリクエスト構造を定義します。\n * @template T - The type of items to be processed.\n */\nexport interface LevenshteinWorkerRequest<T = unknown> {\n    type: \"ping\" | \"setData\" | \"calculateSimilarity\" | \"batchSimilarity\" | \"getStats\" | \"levenshteinSearch\" | \"resetStats\"\n    id: string\n    query?: string\n    items?: T[]\n    searchFields?: string[]\n    candidateIndices?: number[]\n    targets?: string[]\n    target?: string\n    options?: Partial<FuzzySearchOptions>\n    threshold?: number\n    enablePhonetic?: boolean\n}\n\n// ===== Worker-Specific Types =====\n\n/**\n * @interface WorkerSearchStatistics\n * @description Enhanced search statistics provided by a Worker.\n * @description Worker から提供される拡張検索統計。\n */\nexport interface WorkerSearchStatistics {\n    candidatesFound: number\n    indexSize: number\n    ngrams: number\n    searchStrategy: string\n}\n\n/**\n * @interface DetailedWorkerStats\n * @description Detailed performance metrics and statistics from a Worker.\n * @description Worker からの詳細なパフォーマンス指標と統計。\n */\nexport interface DetailedWorkerStats {\n    type: \"stats\"\n    requestId: string\n    workerStats: {\n        totalSearches: number\n        totalIndexBuilds: number\n        currentDataSize: number\n        lastIndexTime: number\n    }\n    memory: {\n        estimatedMemoryUsage: number\n        heapUsage?: number\n        maxMemoryUsage?: number\n    }\n    performanceMetrics: {\n        timings: {\n            averageSearchTime: number\n            averageIndexTime: number\n            maxSearchTime: number\n            minSearchTime: number\n        }\n        throughput: {\n            searchesPerSecond: number\n            indexOperationsPerSecond: number\n        }\n    }\n    indexMetadata?: {\n        totalTokens: number\n        uniqueTokens: number\n        buildTime: number\n        size: number\n    }\n    timestamp: number\n}\n\n/**\n * @interface QueryLengthStat\n * @description Statistics related to query length.\n * @description クエリ長に関連する統計。\n */\nexport interface QueryLengthStat {\n    count: number\n    avgTime: number\n    totalTime: number\n}\n\n/**\n * @interface FieldMatchStat\n * @description Statistics related to matches in specific fields.\n * @description 特定のフィールドでのマッチに関する統計。\n */\nexport interface FieldMatchStat {\n    matches: number\n    avgScore: number\n    totalScore: number\n}\n\n/**\n * @interface SimilarityThresholdStats\n * @description Statistics on the distribution of similarity scores.\n * @description 類似度スコアの分布に関する統計。\n */\nexport interface SimilarityThresholdStats {\n    above80: number\n    above60: number\n    above40: number\n    below40: number\n}\n\n/**\n * @interface PerformanceInsights\n * @description Data providing insights into search performance.\n * @description 検索パフォーマンスに関する洞察を提供するデータ。\n */\nexport interface PerformanceInsights {\n    recentAverageProcessingTime: number\n    recentAverageResultCount: number\n    throughputPerSecond: number\n    totalHistoryEntries: number\n    mostCommonQueryLength: number\n    bestPerformingField: string\n    similarityDistribution: {\n        highSimilarity: number\n        mediumSimilarity: number\n        lowSimilarity: number\n        veryLowSimilarity: number\n    }\n}\n\n/**\n * @interface PerformanceHistoryEntry\n * @description Individual performance history entry for tracking operation performance.\n * @description 操作パフォーマンスを追跡するための個別のパフォーマンス履歴エントリ。\n */\nexport interface PerformanceHistoryEntry {\n    timestamp: number\n    queryLength: number\n    itemCount: number\n    processingTime: number\n    resultCount: number\n    operationType: string\n    additionalMetrics?: Record<string, unknown>\n}\n\n/**\n * @interface FieldStatistic\n * @description Statistics for individual search fields across all operations.\n * @description 全操作における個別検索フィールドの統計。\n */\nexport interface FieldStatistic {\n    matchCount: number\n    averageScore: number\n    totalScore: number\n    bestScore: number\n    worstScore: number\n}\n\n/**\n * @interface UnifiedWorkerStats\n * @description Completely unified statistics interface for all worker types.\n * @description すべてのワーカータイプに対応する完全統一統計インターフェース。\n */\nexport interface UnifiedWorkerStats {\n    /**\n     * @property basic Basic statistics common to all workers.\n     * @description 全ワーカー共通の基本統計。\n     */\n    basic: {\n        totalSearches: number\n        totalProcessingTime: number\n        averageSearchTime: number\n        lastSearchTime: number\n        errorCount: number\n        timestamp: number\n    }\n\n    /**\n     * @property workerSpecific Worker-type specific statistics.\n     * @description ワーカータイプ固有の統計。\n     */\n    workerSpecific: {\n        workerType: \"index\" | \"levenshtein\"\n        operationCount: number\n        operationDistribution: Record<string, number>\n        specificMetrics: Record<string, unknown>\n    }\n\n    /**\n     * @property analysis Advanced analysis and insights.\n     * @description 高度な分析とインサイト。\n     */\n    analysis: {\n        fieldPerformance: Record<string, FieldStatistic>\n        performanceInsights: PerformanceInsights\n        recentHistory: PerformanceHistoryEntry[]\n    }\n}\n\n/**\n * @type WorkerStats\n * @description Unified alias for basic worker statistics.\n * @description 基本ワーカー統計の統一エイリアス。\n */\nexport type WorkerStats = UnifiedWorkerStats[\"basic\"]\n\n/**\n * @type WorkerSpecificStats\n * @description Alias for worker-specific statistics section.\n * @description ワーカー固有統計セクションのエイリアス。\n */\nexport type WorkerSpecificStats = UnifiedWorkerStats[\"workerSpecific\"]\n\n/**\n * @type WorkerAnalysis\n * @description Alias for worker analysis section.\n * @description ワーカー分析セクションのエイリアス。\n */\nexport type WorkerAnalysis = UnifiedWorkerStats[\"analysis\"]\n\n/**\n * @interface WorkerPerformanceMetrics\n * @description Performance metrics for detailed monitoring of a Worker.\n * @description Worker の詳細な監視のためのパフォーマンスメトリクス。\n */\nexport interface WorkerPerformanceMetrics {\n    timings: {\n        averageProcessingTime: number\n        fastestProcessing: number\n        slowestProcessing: number\n        lastProcessingTime: number\n    }\n    throughput: {\n        operationsPerSecond: number\n        totalOperations: number\n    }\n    quality: {\n        successRate: number\n        errorRate: number\n        timeoutRate: number\n    }\n}\n\n// ===== Search Statistics Types =====\n\n/**\n * @interface SearchStats\n * @description Overall search statistics for performance monitoring.\n * @description パフォーマンス監視のための全体的な検索統計。\n */\nexport interface SearchStats {\n    /**\n     * @property {number} totalSearches - Total number of searches performed.\n     * @description 実行された総検索数。\n     */\n    totalSearches: number\n\n    /**\n     * @property {number} averageSearchTime - Average search time in milliseconds.\n     * @description 平均検索時間（ミリ秒）。\n     */\n    averageSearchTime: number\n\n    /**\n     * @property {Array<{ query: string; count: number }>} popularQueries - Popular search queries.\n     * @description 人気のある検索クエリとその実行回数。\n     */\n    popularQueries: Array<{ query: string; count: number }>\n\n    /**\n     * @property {Record<string, { averageTime: number; sampleSize: number }>} performanceBySize - Performance statistics by dataset size.\n     * @description データセットのサイズ別のパフォーマンス統計。\n     */\n    performanceBySize: Record<string, { averageTime: number; sampleSize: number }>\n\n    /**\n     * @property {object} workers - Worker statistics information.\n     * @description 各ワーカーの統計情報。\n     */\n    workers: {\n        index: {\n            stats: UnifiedWorkerStats\n        }\n        levenshtein: {\n            stats: UnifiedWorkerStats\n        }\n    }\n}\n\n/**\n * @interface SearchStatistics\n * @description Search statistics provided by a worker.\n * @description Worker から提供される検索統計。\n */\nexport interface SearchStatistics {\n    candidatesFound: number\n    indexSize: number\n    ngrams: number\n    words?: number\n    phonetic?: number\n    searchStrategy: string\n}\n\n/**\n * @interface SearchHistory\n * @description Represents a single entry in the search history for learning and analytics.\n * @description 学習と分析のための検索履歴の単一エントリを表します。\n */\nexport interface SearchHistory {\n    /**\n     * @property {string} query - The search query.\n     * @description 検索クエリ。\n     */\n    query: string\n\n    /**\n     * @property {number} timestamp - Timestamp of the search.\n     * @description 検索が実行されたときのタイムスタンプ。\n     */\n    timestamp: number\n\n    /**\n     * @property {number} resultCount - Number of results found.\n     * @description 見つかった結果の数。\n     */\n    resultCount: number\n\n    /**\n     * @property {number} processingTime - Processing time in milliseconds.\n     * @description 処理にかかった時間（ミリ秒）。\n     */\n    processingTime: number\n\n    /**\n     * @property {number} [searchTime] - Alias for processingTime.\n     * @description processingTime のエイリアス。\n     */\n    searchTime?: number\n\n    /**\n     * @property {number} [selectedIndex] - Index of the selected result, if any.\n     * @description ユーザーが選択した結果のインデックス（存在する場合）。\n     */\n    selectedIndex?: number\n\n    /**\n     * @property {string} [selectedItemId] - ID of the selected item, if any.\n     * @description ユーザーが選択したアイテムのID（存在する場合）。\n     */\n    selectedItemId?: string\n\n    /**\n     * @property {number} [satisfactionScore] - User satisfaction score (1-5).\n     * @description ユーザー満足度スコア（1-5）。\n     */\n    satisfactionScore?: number\n\n    /**\n     * @property {boolean} successful - Whether the search was considered successful.\n     * @description 検索が成功したと見なされたかどうか。\n     */\n    successful: boolean\n\n    /**\n     * @property {string} [context] - Context or source of the search.\n     * @description 検索が実行されたコンテキストまたはソース。\n     */\n    context?: string\n}\n\n/**\n * @interface LearningData\n * @description Data structure for storing learned information to improve search results.\n * @description 検索結果を改善するために学習した情報を格納するためのデータ構造。\n */\nexport interface LearningData {\n    /**\n     * @property {Record<string, number>} fieldWeights - Field-specific weights learned from user behavior.\n     * @description ユーザーの行動から学習したフィールド固有の重み。\n     */\n    fieldWeights: Record<string, number>\n\n    /**\n     * @property {Record<string, number>} queryPatterns - Query patterns and their frequency count.\n     * @description クエリのパターンとその出現頻度。\n     */\n    queryPatterns: Record<string, number>\n\n    /**\n     * @property {object} userPreferences - User preferences and behavior.\n     * @description ユーザーの好みと行動の記録。\n     */\n    userPreferences: {\n        preferredThreshold: number\n        frequentFields: string[]\n        searchStyle: \"exact\" | \"fuzzy\" | \"mixed\"\n        lastUsedOptions: Partial<FuzzySearchOptions>\n    }\n\n    /**\n     * @property {object} performanceMetrics - Performance metrics for learning optimization.\n     * @description 学習の最適化に使用されるパフォーマンス指標。\n     */\n    performanceMetrics: {\n        averageSearchTime: Record<string, number>\n        indexBuildTime: number\n    }\n}\n\n// ===== Utility Types =====\n\n/**\n * @type ExtractItemType\n * @description Utility type to extract the item type from a SearchResultItem.\n * @description SearchResultItem からアイテムの型を抽出するためのユーティリティ型。\n * @template T - The type of the SearchResultItem.\n */\nexport type ExtractItemType<T> = T extends SearchResultItem<infer U> ? U : never\n\n/**\n * @type SearchFields\n * @description Defines the search fields with type safety, accepting keys of T or strings.\n * @description 型安全性を備えた検索フィールドを定義します。T のキーまたは文字列を受け入れます。\n * @template T - The type of the items being searched.\n */\nexport type SearchFields<T> = Array<keyof T | string>\n\n/**\n * @type SearchResultCallback\n * @description Callback function type for handling search results.\n * @description 検索結果を処理するためのコールバック関数型。\n * @template T - The type of the items in the results.\n */\nexport type SearchResultCallback<T> = (results: SearchResults<T>) => void\n\n// ===== Type Guards =====\n\n/**\n * @function isSearchResultItem\n * @description Type guard to check if an object is a SearchResultItem.\n * @description オブジェクトが SearchResultItem かどうかをチェックする型ガード。\n * @param {unknown} obj - The object to check.\n * @returns {boolean} - True if the object is a SearchResultItem.\n * @template T - The expected type of the item within the SearchResultItem.\n */\nexport function isSearchResultItem<T>(obj: unknown): obj is SearchResultItem<T> {\n    // オブジェクトであり、null でなく、必須プロパティが存在するかをチェック\n    return typeof obj === \"object\" && obj !== null && \"item\" in obj && \"score\" in obj && \"matchedFields\" in obj\n}\n\n// ===== React Hook Types =====\n\n/**\n * @type UseFuzzySearchOptions\n * @description Options type for the useFuzzySearch hook, extending PartialFuzzySearchOptions.\n * @description useFuzzySearch フック用のオプション型。PartialFuzzySearchOptions を拡張します。\n */\nexport type UseFuzzySearchOptions = PartialFuzzySearchOptions\n\n/**\n * @interface SearchHistoryResult\n * @description The return type for a hook that manages search history.\n * @description 検索履歴を管理するフックの戻り値の型。\n */\nexport interface SearchHistoryResult {\n    searchHistory: SearchHistory[]\n    addToHistory: (term: string) => void\n    clearHistory: () => void\n}\n\n/**\n * @interface PerformanceMetrics\n * @description Data type for the performance metrics callback.\n * @description パフォーマンス指標コールバック用のデータ型。\n */\nexport interface PerformanceMetrics {\n    totalSearches: number\n    averageSearchTime: number\n    itemCount: number\n    resultsCount: number\n    workerStats?: {\n        index?: UnifiedWorkerStats\n        levenshtein?: UnifiedWorkerStats\n    }\n}\n\n/**\n * @interface FuzzySearchResult\n * @description The return type for the simplified fuzzy search hook.\n * @description 簡易版のあいまい検索フックの戻り値の型。\n * @template T - The type of the items being searched.\n */\nexport interface FuzzySearchResult<T> {\n    searchTerm: string\n    setSearchTerm: (term: string) => void\n    filteredItems: SearchResultItem<T>[]\n    isSearching: boolean\n    isIndexBuilding: boolean\n    error: string | null\n    searchHistory: SearchHistory[]\n    options: FuzzySearchOptions\n    selectItem: (item: T, index: number) => void\n    clearSearch: () => void\n    clearHistory: () => void\n    resetStats: () => Promise<void>\n    getSearchSuggestions: (query: string, limit?: number) => string[]\n    performanceMetrics: PerformanceMetrics\n    rebuildIndex: (customOptions?: UseFuzzySearchOptions) => Promise<void>\n}\n","/**\n * Common types and utilities for fuzzy search workers.\n * あいまい検索ワーカー用の共通型とユーティリティ。\n */\n\nimport type { FieldStatistic, PerformanceHistoryEntry, PerformanceInsights, UnifiedWorkerStats, WorkerPerformanceMetrics, WorkerStats } from \"../types/index\"\n\nconst LOG_PREFIX = \"[fuzzy-search]\"\n\n/**\n * Provides a base class for workers with common functionality for statistics and performance metrics.\n * This class is intended to be extended by specific worker implementations.\n * 統計およびパフォーマンスメトリクスの共通機能を備えたワーカーの基本クラスを提供します。\n * このクラスは、特定のワーカー実装によって拡張されることを意図しています。\n */\nexport abstract class BaseWorker {\n    /**\n     * Stores basic statistics about the worker's operations.\n     * ワーカーの操作に関する基本的な統計を保存します。\n     */\n    protected stats: WorkerStats = {\n        totalSearches: 0,\n        totalProcessingTime: 0,\n        averageSearchTime: 0,\n        lastSearchTime: 0,\n        errorCount: 0,\n        timestamp: Date.now(),\n    }\n\n    /**\n     * Unified detailed statistics for all worker types.\n     * 全ワーカータイプの統一詳細統計。\n     */\n    protected detailedStats: Map<string, unknown> = new Map()\n    protected performanceHistory: PerformanceHistoryEntry[] = []\n    protected operationDistribution: Map<string, number> = new Map()\n    protected fieldStats: Map<string, FieldStatistic> = new Map()\n\n    /**\n     * Stores detailed performance metrics of the worker.\n     * ワーカーの詳細なパフォーマンスメトリクスを保存します。\n     */\n    protected metrics: WorkerPerformanceMetrics = {\n        timings: {\n            averageProcessingTime: 0,\n            fastestProcessing: Infinity,\n            slowestProcessing: 0,\n            lastProcessingTime: 0,\n        },\n        throughput: {\n            operationsPerSecond: 0,\n            totalOperations: 0,\n        },\n        quality: {\n            successRate: 1,\n            errorRate: 0,\n            timeoutRate: 0,\n        },\n    }\n\n    /**\n     * Updates the statistics and performance metrics after an operation.\n     * @param processingTime The time taken for the operation in milliseconds.\n     * @param success A boolean indicating if the operation was successful.\n     * 操作後に統計およびパフォーマンスメトリクスを更新します。\n     * @param processingTime 操作にかかった時間（ミリ秒）。\n     * @param success 操作が成功したかどうかを示すブール値。\n     */\n    protected updateStats(processingTime: number, success: boolean = true): void {\n        // 基本的な統計を更新します\n        this.stats.totalSearches++\n        this.stats.totalProcessingTime += processingTime\n        this.stats.averageSearchTime = this.stats.totalProcessingTime / this.stats.totalSearches\n        this.stats.lastSearchTime = processingTime\n\n        // タイミングメトリクスを更新します\n        this.metrics.timings.lastProcessingTime = processingTime\n        this.metrics.timings.averageProcessingTime = this.stats.averageSearchTime\n        this.metrics.timings.fastestProcessing = Math.min(this.metrics.timings.fastestProcessing, processingTime)\n        this.metrics.timings.slowestProcessing = Math.max(this.metrics.timings.slowestProcessing, processingTime)\n\n        // スループットメトリクスを更新します\n        this.metrics.throughput.totalOperations++\n        if (this.metrics.timings.averageProcessingTime > 0) {\n            this.metrics.throughput.operationsPerSecond = 1000 / this.metrics.timings.averageProcessingTime\n        }\n\n        // 失敗した場合、エラーカウントをインクリメントします\n        if (!success) {\n            this.stats.errorCount++\n        }\n\n        // 品質メトリクスを更新します\n        const totalOps = this.metrics.throughput.totalOperations\n        this.metrics.quality.successRate = (totalOps - this.stats.errorCount) / totalOps\n        this.metrics.quality.errorRate = this.stats.errorCount / totalOps\n    }\n\n    /**\n     * Gets a copy of the current worker statistics.\n     * @returns An object containing the worker's statistics.\n     * 現在のワーカ統計のコピーを取得します。\n     * @returns ワーカーの統計を含むオブジェクト。\n     */\n    getStats(): WorkerStats {\n        // 統計オブジェクトのコピーを返します\n        return { ...this.stats }\n    }\n\n    /**\n     * Gets a copy of the current worker performance metrics.\n     * @returns An object containing the worker's performance metrics.\n     * 現在のワーカーパフォーマンスメトリクスのコピーを取得します。\n     * @returns ワーカーのパフォーマンスメトリクスを含むオブジェクト。\n     */\n    getMetrics(): WorkerPerformanceMetrics {\n        // メトリクスオブジェクトのコピーを返します\n        return { ...this.metrics }\n    }\n\n    /**\n     * Resets all worker statistics and performance metrics to initial state.\n     * This method can be overridden by child classes to reset worker-specific statistics.\n     * 全ての統計情報とパフォーマンスメトリクスを初期状態にリセットします。\n     * このメソッドは子クラスで固有統計をリセットするためにオーバーライドできます。\n     */\n    resetStats(): void {\n        // 基本統計をリセット\n        this.stats = {\n            totalSearches: 0,\n            totalProcessingTime: 0,\n            averageSearchTime: 0,\n            lastSearchTime: 0,\n            errorCount: 0,\n            timestamp: Date.now(),\n        }\n\n        // パフォーマンスメトリクスをリセット\n        this.metrics = {\n            timings: {\n                averageProcessingTime: 0,\n                fastestProcessing: Infinity,\n                slowestProcessing: 0,\n                lastProcessingTime: 0,\n            },\n            throughput: {\n                operationsPerSecond: 0,\n                totalOperations: 0,\n            },\n            quality: {\n                successRate: 1,\n                errorRate: 0,\n                timeoutRate: 0,\n            },\n        }\n\n        // 統一統計をリセット\n        this.detailedStats.clear()\n        this.performanceHistory = []\n        this.operationDistribution.clear()\n        this.fieldStats.clear()\n\n        console.log(`${LOG_PREFIX} 📊 ${this.getWorkerType()} Worker: Statistics reset completed`)\n    }\n\n    /**\n     * Updates unified worker statistics with operation-specific data.\n     * @param operationType The type of operation performed.\n     * @param processingTime The time taken for the operation.\n     * @param additionalData Additional metrics specific to the operation.\n     * 操作固有データで統一ワーカー統計を更新します。\n     * @param operationType 実行された操作のタイプ。\n     * @param processingTime 操作にかかった時間。\n     * @param additionalData 操作固有の追加メトリクス。\n     */\n    protected updateWorkerStats(operationType: string, processingTime: number, additionalData: Record<string, unknown> = {}): void {\n        // 基本統計更新\n        this.updateStats(processingTime, true)\n\n        // 操作統計更新\n        const currentCount = this.operationDistribution.get(operationType) || 0\n        this.operationDistribution.set(operationType, currentCount + 1)\n\n        // 詳細データ保存\n        Object.entries(additionalData).forEach(([key, value]) => {\n            this.detailedStats.set(key, value)\n        })\n\n        // パフォーマンス履歴追加\n        this.addPerformanceEntry({\n            timestamp: Date.now(),\n            operationType,\n            processingTime,\n            queryLength: (additionalData.queryLength as number) || 0,\n            itemCount: (additionalData.itemCount as number) || 0,\n            resultCount: (additionalData.resultCount as number) || 0,\n            additionalMetrics: additionalData,\n        })\n    }\n\n    /**\n     * Updates field-specific statistics.\n     * @param field The search field name.\n     * @param score The match score for this field.\n     * フィールド固有の統計を更新します。\n     * @param field 検索フィールド名。\n     * @param score このフィールドのマッチスコア。\n     */\n    protected updateFieldStats(field: string, score: number): void {\n        const current = this.fieldStats.get(field) || {\n            matchCount: 0,\n            averageScore: 0,\n            totalScore: 0,\n            bestScore: 0,\n            worstScore: 1,\n        }\n\n        current.matchCount += 1\n        current.totalScore += score\n        current.averageScore = current.totalScore / current.matchCount\n        current.bestScore = Math.max(current.bestScore, score)\n        current.worstScore = Math.min(current.worstScore, score)\n\n        this.fieldStats.set(field, current)\n    }\n\n    /**\n     * Adds a performance history entry with size limit.\n     * @param entry The performance entry to add.\n     * サイズ制限付きでパフォーマンス履歴エントリを追加します。\n     * @param entry 追加するパフォーマンスエントリ。\n     */\n    protected addPerformanceEntry(entry: PerformanceHistoryEntry): void {\n        this.performanceHistory.push(entry)\n\n        // 履歴のサイズ制限（最新100件）\n        if (this.performanceHistory.length > 100) {\n            this.performanceHistory = this.performanceHistory.slice(-100)\n        }\n    }\n\n    /**\n     * Gets unified worker statistics including all analysis data.\n     * @returns Complete unified statistics for this worker.\n     * すべての分析データを含む統一ワーカー統計を取得します。\n     * @returns このワーカーの完全な統一統計。\n     */\n    public getWorkerStats(): UnifiedWorkerStats {\n        return {\n            basic: {\n                ...this.stats,\n                timestamp: Date.now(),\n            },\n            workerSpecific: {\n                workerType: this.getWorkerType(),\n                operationCount: this.getTotalOperations(),\n                operationDistribution: Object.fromEntries(this.operationDistribution),\n                specificMetrics: this.getSpecificMetrics(),\n            },\n            analysis: {\n                fieldPerformance: Object.fromEntries(this.fieldStats),\n                performanceInsights: this.generatePerformanceInsights(),\n                recentHistory: this.performanceHistory.slice(-10),\n            },\n        }\n    }\n\n    /**\n     * Sends unified statistics update to the main thread.\n     * メインスレッドに統一統計更新を送信します。\n     */\n    protected sendStatsUpdate(): void {\n        const response = {\n            type: \"stats\",\n            id: `stats-${Date.now()}`,\n            stats: this.getWorkerStats(),\n            metrics: this.getMetrics(),\n            processingTime: 0,\n            workerType: this.getWorkerType(),\n            operationMeta: {},\n        }\n\n        console.log(`${LOG_PREFIX} 📊 ${this.getWorkerType()} Worker: Sending unified stats update`)\n        self.postMessage(response)\n    }\n\n    // 抽象メソッド - 子クラスで実装が必要\n    protected abstract getWorkerType(): \"index\" | \"levenshtein\"\n    protected abstract getSpecificMetrics(): Record<string, unknown>\n\n    /**\n     * Gets the total number of operations performed by this worker.\n     * @returns The total operation count.\n     * このワーカーが実行した操作の総数を取得します。\n     * @returns 総操作数。\n     */\n    protected getTotalOperations(): number {\n        return Array.from(this.operationDistribution.values()).reduce((sum, count) => sum + count, 0)\n    }\n\n    /**\n     * Generates performance insights from historical data.\n     * @returns Performance insights object.\n     * 履歴データからパフォーマンスインサイトを生成します。\n     * @returns パフォーマンスインサイトオブジェクト。\n     */\n    protected generatePerformanceInsights(): PerformanceInsights {\n        if (this.performanceHistory.length === 0) {\n            return {\n                recentAverageProcessingTime: 0,\n                recentAverageResultCount: 0,\n                throughputPerSecond: 0,\n                totalHistoryEntries: 0,\n                mostCommonQueryLength: 0,\n                bestPerformingField: \"\",\n                similarityDistribution: {\n                    highSimilarity: 0,\n                    mediumSimilarity: 0,\n                    lowSimilarity: 0,\n                    veryLowSimilarity: 0,\n                },\n            }\n        }\n\n        const recent = this.performanceHistory.slice(-10)\n        const avgProcessingTime = recent.reduce((sum, h) => sum + h.processingTime, 0) / recent.length\n        const avgResultCount = recent.reduce((sum, h) => sum + h.resultCount, 0) / recent.length\n\n        // 最も一般的なクエリ長を計算\n        const queryLengths = new Map<number, number>()\n        this.performanceHistory.forEach((entry) => {\n            const current = queryLengths.get(entry.queryLength) || 0\n            queryLengths.set(entry.queryLength, current + 1)\n        })\n\n        let mostCommonQueryLength = 0\n        let maxCount = 0\n        queryLengths.forEach((count, length) => {\n            if (count > maxCount) {\n                maxCount = count\n                mostCommonQueryLength = length\n            }\n        })\n\n        // 最高パフォーマンスフィールドを計算\n        let bestField = \"\"\n        let bestScore = 0\n        this.fieldStats.forEach((stat, field) => {\n            if (stat.averageScore > bestScore) {\n                bestScore = stat.averageScore\n                bestField = field\n            }\n        })\n\n        return {\n            recentAverageProcessingTime: avgProcessingTime,\n            recentAverageResultCount: avgResultCount,\n            throughputPerSecond: avgProcessingTime > 0 ? 1000 / avgProcessingTime : 0,\n            totalHistoryEntries: this.performanceHistory.length,\n            mostCommonQueryLength,\n            bestPerformingField: bestField,\n            similarityDistribution: {\n                highSimilarity: 0,\n                mediumSimilarity: 0,\n                lowSimilarity: 0,\n                veryLowSimilarity: 0,\n            },\n        }\n    }\n\n    /**\n     * Placeholder for handling messages from the main thread. This should be overridden by child classes.\n     * @param _event The message event.\n     * メインスレッドからのメッセージを処理するためのプレースホルダー。子クラスでオーバーライドする必要があります。\n     * @param _event メッセージイベント。\n     */\n    handleMessage(_event: MessageEvent): void {\n        // デフォルト実装 - 子クラスでオーバーライドする必要があります\n        console.warn(`${LOG_PREFIX} ⚠️ BaseWorker.handleMessage: No implementation provided`)\n    }\n}\n","/**\n * Index Strategy Web Worker for fuzzy search.\n * あいまい検索用のインデックス戦略Web Worker。\n *\n * This worker specializes in building and managing search indices,\n * candidate filtering, and index-based optimizations.\n * このワーカーは検索インデックスの構築・管理、候補フィルタリング、\n * インデックスベースの最適化に特化しています。\n */\n\nimport type { FuzzySearchOptions, IndexMetadata, IndexWorkerRequest, PerformanceInsights, SearchResultItem, SimilarityThresholdStats, UnifiedWorkerResponse } from \"../types/index\"\nimport { DEFAULT_FUZZY_SEARCH_OPTIONS } from \"../types/index\"\nimport { BaseWorker } from \"./common\"\n\nconst LOG_PREFIX = \"[fuzzy-search]\"\n\n/**\n * Implements the index strategy worker.\n * インデックス戦略ワーカーを実装します。\n */\nclass IndexStrategyWorker extends BaseWorker {\n    // 複合インデックスキャッシュ\n    private ngramCache = new Map<string, Set<number>>()\n    private wordCache = new Map<string, Set<number>>()\n    private phoneticCache = new Map<string, Set<number>>()\n\n    // データキャッシュ\n    private currentItems: unknown[] = []\n    private currentSearchFields: string[] = []\n    private indexMetadata: IndexMetadata | null = null\n\n    // Index Worker 専用統計\n    private indexStats = {\n        totalIndexBuilds: 0,\n        currentDataSize: 0,\n        lastIndexTime: 0,\n    }\n\n    // 類似度分布統計\n    private similarityThresholdStats: SimilarityThresholdStats = {\n        above80: 0,\n        above60: 0,\n        above40: 0,\n        below40: 0,\n    }\n\n    /**\n     * Gets the worker type for unified statistics.\n     * @returns The worker type identifier.\n     * 統一統計用のワーカータイプを取得します。\n     * @returns ワーカータイプ識別子。\n     */\n    protected getWorkerType(): \"index\" {\n        return \"index\"\n    }\n\n    /**\n     * Gets worker-specific metrics for unified statistics.\n     * @returns Worker-specific metrics object.\n     * 統一統計用のワーカー固有メトリクスを取得します。\n     * @returns ワーカー固有メトリクスオブジェクト。\n     */\n    protected getSpecificMetrics(): Record<string, unknown> {\n        return {\n            totalIndexBuilds: this.indexStats.totalIndexBuilds,\n            currentDataSize: this.indexStats.currentDataSize,\n            lastIndexTime: this.indexStats.lastIndexTime,\n            cacheSize: {\n                ngram: this.ngramCache.size,\n                word: this.wordCache.size,\n                phonetic: this.phoneticCache.size,\n            },\n            indexMetadata: this.indexMetadata || {},\n            similarityThresholds: { ...this.similarityThresholdStats },\n        }\n    }\n\n    /**\n     * Resets only Index Worker specific statistics to initial state.\n     * Index Worker 固有の統計情報のみを初期状態にリセットします。\n     */\n    resetStats(): void {\n        // 基底クラスの統計リセット\n        super.resetStats()\n\n        // Index Worker 固有の統計をリセット\n        this.indexStats = {\n            totalIndexBuilds: 0,\n            currentDataSize: 0,\n            lastIndexTime: 0,\n        }\n\n        // 類似度統計をリセット\n        this.similarityThresholdStats = {\n            above80: 0,\n            above60: 0,\n            above40: 0,\n            below40: 0,\n        }\n\n        console.log(`${LOG_PREFIX} 🔧 Index Worker: All statistics reset completed`)\n    }\n\n    /**\n     * Updates similarity threshold statistics based on the score.\n     * @param score The similarity score (0-1).\n     * スコアに基づいて類似度しきい値統計を更新します。\n     * @param score 類似度スコア (0-1)。\n     */\n    private updateSimilarityStats(score: number): void {\n        if (score >= 0.8) {\n            this.similarityThresholdStats.above80++\n        } else if (score >= 0.6) {\n            this.similarityThresholdStats.above60++\n        } else if (score >= 0.4) {\n            this.similarityThresholdStats.above40++\n        } else {\n            this.simila