隨著全球化的趨勢，英語對於非英語系的國家來說愈來愈重要，而近年來，已經有許多學習者利用閱讀英文文章的方式來幫助自己學習英文。但對於一般的學習者來說，如何去選擇一篇自己感興趣而又難度適中的英文文章來做學習是不容易的。
本研究提出一個以模糊推論為基礎的英文新聞文章推薦系統，其主要是利用模糊推論機制(Fuzzy Inference Mechanism)、記憶週期(Memory Cycle)的概念、學習者的興趣指數以及層級分析法(Analytic Hierarchy Process, AHP)來找出適當的英文新聞文章推薦給學習者閱讀學習。
透過學習成就以及問卷分析，證實本研究所提出來的方法的確可以提升學習者的英文能力，並且提高學習者的學習興趣，以達到適性學習的效果。

With the trend of globalization, English is more and more important to English as a Foreign Language (EFL) people. In years, many English learners used to read articles in order to help themselves studying English. But, choosing suitable articles in accordance with learners’ needs and interests is actually difficult. This thesis proposes a fuzzy logic based English document recommendation system which recommends appropriate English news to learners by harnessing Fuzzy Inference Mechanism, memory cycle update, learners’ preferences, and Analytic Hierarchy Process (AHP). The analysis of learners’ achievements and questionnaires has confirmed the method of this study not only enhances learners’ English ability but also enhances learners’ learning interest by the effect of adaptive learning.

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