面對現今產業競爭愈加劇烈的狀況，各企業除了在成本、品質、產品上積極改善之外，也引進了以顧客為主的思維來改善產品與服務。以顧客為出發點，可以更瞭解真正的需求為何，讓顧客的滿意度提高。隨著資訊科技的發展，讓這樣的想法得以具體化。於是，顧客關係管理系統興起，可以有效率地得知顧客的需求；甚至從購買的行為找出特殊的關聯、預測可能的行為模式，進而早一步制訂合適的策略，來提升顧客滿意度。
顧客在購買產品或服務之後，可能會有抱怨或建議的狀況發生。針對這些抱怨問題，企業必須要妥善處理，才能提昇顧客滿意度及忠誠度。顧客的抱怨文件中，隱含許多寶貴的資訊，可以作為企業的知識庫及決策的參考，並回饋給顧客最佳的解決方法。因此，從非結構化的客訴文件中去找出可能的關聯是本研究所關心的，並試圖將這些資訊予以外顯化、具體化，以便可以實際運用於顧客關係管理的改善。
本研究由文件管理的角度出發，配合文件探勘的相關技術，從顧客抱怨文件中分析出各文件的關鍵詞彙，並以此為基礎來探勘其關聯法則。由於文件中詞彙出現的頻率並不足以代表其關鍵概念，因此本研究以相關背景知識建立概念階層架構，用來輔助探勘的進行。各關聯的相關程度則以各詞彙出現的機率來加以判斷，以區別出各關聯法則的正確度。

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