專利的功能除了保護發明者的智慧心血不被侵害之外，對於企業在日漸激烈的商業環境上也愈顯重要。然而許多國家的專利制度，在專利申請獲准之後，必須要定期繳交維護費用，才能確保此專利在期限內仍然有作用。然而，並非所有的專利都需要進行維護。對於企業而言，找出「重要專利」進行維護，並將「不重要專利」進行放棄，這同時包含許多不同的決策思維。本研究預計透過德菲法(Delphi method)獲得實務上認為會影響專利是否維護的因素，且運用資料探勘的方式建立系統支援專利維護決策。這種以資料探勘為基礎的專利維護決策系統，可以協助組織在進行維護決策時，增進其效率且降低維護決策的成本。實證結果顯示，我們所提出的維護模型表現優於基準模型(所使用的變數僅由文獻中所建議組成)。

Protecting the rights of inventor is not the only purpose of patents, and it is becoming more and more important under the keen competitive business environment nowadays. In the patent systems of many countries, patent holders are required to pay a maintenance fee after the initial application to retain patent protection on any invention until the expiration of the protection period. However, not all patents are worth maintaining by patent holders. Thus, organizations need to identify “important patents” for maintenance and abandon “unimportant patents.” In this study, we attempt to examine factors influencing patent maintenance via a Delphi study and propose a data mining approach to support patent maintenance decision. Such a data-mining-based patent maintenance decision support system can help organizations improve the effectiveness of patent maintenance decisions and, at the same time, decrease the cost of maintenance decision. Our empirical evaluation results suggest that our proposed model outperforms the benchmark model (i.e., involving the variables suggested by the literature only).

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