7.1 結論
本研究提出對於關聯式資料庫之關鍵字查詢處理技術，是將查詢關鍵字進行 拆解，拆解成一至多個查詢條件並且分組。接著透過給定設計查詢條件單位以邏 輯運算子組合運算的優先順序指定括弧位置，產生最可能表達使用者給予關鍵字 查詢的搜尋意圖的條件組合，最後再轉換成所對應的 SQL 查詢語句，並且執行於 關聯式資料庫。此外，我們根據該查詢條件所得到的查詢結果，依統計觀點提供 具有一致性和分佈變化量大幅改變的特殊資料摘要呈現給使用者。
實驗中評估本研究所提出方法能處理的關鍵字查詢之轉換正確率，透過控制 型和非控制型的實驗結果得到，在多數情況下能正確處理查詢型態為在單一屬性 值、資料型態和屬性值組合、數值條件式的查詢。在查詢結果摘要的部分，所提 出根據一致性和分佈變化差異的摘要方法，對於使用者得知隱含在查詢結果的重 要資訊也是有幫助。
7.2 未來研究方向
本研究自動將關鍵字和數值條件式描述的查詢轉換成結構化查詢語言的
SQL 語句時，只考慮 基本資料庫查 詢條件句型 ，未來可增 加像是 聚合 函數
(aggregation functions)，例如：Avg、Count、Min、Max 等，可提供更多樣化的查 詢功能。
此外，現階段並沒有考慮查詢關鍵字和資料庫綱目或資料庫內容上，文字不 同卻有語意關聯接近的情形。若能利用一個外部參考資源去輔助處理語意，查詢 關鍵字和資料庫綱目比對或是查詢關鍵字和資料庫內容比對時，除了字詞上完全 比對之外，還可處理使用者下查詢關鍵字中所對應相似字的詞彙，能更有彈性甚 至找出更多相關性結果。也可先行收集使用者過往所輸入過的查詢關鍵字，利用 查詢記錄檔(Query Log)去得知使用者使用查詢關鍵字的使用習慣，了解使用者輸 入查詢關鍵字時，通常最可能所表達的意圖為何，對於查詢意圖上的分析能更有 幫助。
在查詢結果摘要部份，則可考量以其他方法觀點做摘要，不僅只從查詢結果 的統計資訊做分析。依照本論文所提出之處理方式，得知查詢結果後，再開始統 計該查詢結果的各個相關統計資訊，需要處理時間而無法立即呈現給使用者。若 所需要的參考資訊能從事先建立的資訊去做分析，對於摘要即時呈現的角度而言，
才可以進一步提昇摘要時的處理效率。
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