在本論文中，我們提出根據模糊推理及知識本體以自動產生中文新聞摘要的新方法，在此方法中，我們所引用的知識本體由各領域專家定義，分別為氣象知識本體、時間知識本體和地理知識本體，其中我們將中文氣象新聞文章分割為一組詞的集合，根據兩個知識本體的特徵(亦即：知識本體的深度和知識本體的廣度)及一個統計上的特徵(亦即：頻率)作為系統的輸入參數，此三個參數以模糊集合表示並以模糊推理以推理出每個句子的分數，以作為評斷此句子是否適合作為摘要的依據，最後產生之氣象新聞摘要由分數較高的句子所組成。本論文的實驗資料採用台灣的氣象新聞網站，實驗結果顯示此新方法比目前已存在之方法和有更佳的性能以自動產生中文氣象新聞摘要。

In this thesis, we present a new method for automatically generating the Chinese weather news summary based on fuzzy reasoning and the domain ontology, where the weather ontology, the time ontology and the geography ontology are predefined by domain experts. We slice the original Chinese weather news articles into a set of terms. Then, we use two ontological features (i.e., the degree of depth of the ontology and the degree of width of the ontology) and one statistical feature (i.e., the frequency) as inputs of the system. The values of those features are represented by fuzzy sets. Then, the fuzzy reasoning mechanism calculates the score of each sentence. The summary is composed of candidate sentences which have higher scores, where the experimental data are adopted from the Chinese weather news website of Taiwan. The experimental results show that the proposed method outperforms the methods presented in [14] and [15] for automatically generating the Chinese news summary.

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