本文著重於專利資料的分類以及針對分類完成之專利資料進行管理及分析，應用貝氏理論及模糊邏輯之相關技術，建構出一個專利分類模式，來協助使用者對於大量專利資料進行分類管理，並且應用層級程序分析法對分類完成之專利資料進行技術及功能導向趨勢之分析。首先透過專利資料庫蒐集相關知識的專利資料內容，配合相關工程知識以及專利語意分析方法，定義出所屬之知識領域分類類別，並從專利內容中過濾出對應到各類別之相關代表詞彙，進一步建構出以本體論為精神的階層式分類模型，其分層概念從系統元件層分類，到工程意義層分類，進而進行技術及功能分類，依據此模型將專利文件依其所屬之知識領域進行分類。最後，即可依據階層式類別模型中之技術及功能類別層分類結果，建構出技術功效矩陣表的形式，透過此表的建立，可達到快速取得相關技術的專利資料及縮短研發的時間，並且可應用層級程序分析法對技術及功能之導向趨勢進行分析，分析後所得到的結果，可用來協助決定未來創新研發之發展方向。

This paper focuses its study on the classification of patent information, and then manages and analyzes the patent information having completed classification. By using the related technologies of Bayesian Theory and fuzzy logic, the study constructs a patent classification model to help users conduct classification and management of large volume of patent information. Analytic hierarchy process is also applied to analyze the technology and function orientation trend of the classified patent information. Through the contents of related patent knowledge and information in the patent database, together with the related engineering knowledge and patent semiotics analysis, the study defines the categories of the various knowledge realms, filters our the related representative vocabularies of the corresponding categories from the patent contents, and further constructs the ontology-based hierarchal classification model. The classification concept is to classify from the hierarchy of system components to the hierarchy of engineering meanings, and further conduct technical and functional classification. Based on this model, patent documents are classified according to their knowledge realms. Finally, according to the hierarchal classification results of technical and functional categories in the hierarchical category model, the study constructs a form of technical effect matrix. With this matrix, we can quickly acquire the patent information of the related technology, and shorten the time of research and development. Besides, analytic hierarchy process can be applied to analyze the technology and function orientation trend. The analytic results can be used to assist in determining the development direction of future innovative research and development.

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