近年來受環境變遷影響而頻傳氣候災害，使得環保意識逐漸抬頭以及衍生出國際間諸多新興議題與倡議如碳權(碳稅、碳交易)、ESG、SDGs、巴黎協定、京都協定書、2050淨零碳排等，人們已不再一昧發展經濟而是在發展過程中尋求與環境的平衡。資訊與通訊技術(Information and Communication Technology, ICT)產業作為我國重點發展產業擁有技術領先與產業鏈完整等特性，提供了豐富的技術、專利等資訊利於進行知識管理與專利分析，為順應國際間淨零與減碳潮流以鞏固既有優勢產業，本研究旨在利用網路分析探索ICT產業內循環經濟相關淨零技術與專利佈局，以此了解我國ICT產業發展現況、商業應用趨勢、與他國研發熱點差異等。研究首先透過文獻計量分析、本體論工程將收集到的相關專利制定出初步的本體，並依據建立之本體擬定專利搜索策略，再以關鍵字萃取的專利文本資料與專利間引用關係的圖結構資料輸入圖注意力網路(graph attention networks, GATs)以輸出嵌入向量，最後以分群演算法得到群集專利後，即可以社群網路分析(social network analysis, SNA)的多個指標分次進行群集專利間與群集內專利的詳細分析，如專利分類、識別專利社群結構、識別專利群集內重要專利等。本研究使用一套通用性的分析方法，收集、分析與探索全球ICT產業專利、技術，提供目前領域內技術發展趨勢、國內專利佈局與全球研發重點差異等資訊幫助整合研發資源、合理配置投資，同時透過本體視覺化的方式概觀呈現ICT產業內循環經濟淨零相關技術類別。

In recent years, climate disasters have become more frequent due to the impact of environmental changes. This has led to an increasing environmental consciousness and the emergence of various international issues and initiatives such as carbon rights (carbon taxes, carbon trading), ESG (Environmental, Social, and Governance), SDGs (Sustainable Development Goals), the Paris Agreement, the Kyoto Protocol, and achieving net-zero carbon emissions by 2050. People are no longer solely focused on economic development but are now seeking a balance with the environment. The Information and Communication Technology (ICT) industry, as a key development sector in our country, boasts characteristics such as technological leadership and a complete industry supply chain. It provides a wealth of technical information and patents, making it conducive for knowledge management and patent analysis. This research aims to utilize network analysis to explore net-zero technology and patents landscape related to circular economy within the ICT industry. The goal is to understand the current status of ICT industry development in our country, commercial application trends, and differences in research and development focus compared to other countries. This aligns with the international trends toward achieving net-zero emissions and carbon reduction while strengthening existing advantageous industries. The study begins by conducting literature-based quantitative analysis and ontology engineering to develop initial ontologies based on collected relevant patents. Subsequently, a patent search strategy is formulated according to the established ontology, followed by inputting patent text data extracted by keyword and the graph structure data of patent citations into Graph Attention Networks (GATs) to output embedded vectors. Finally, through clustering algorithms, clustered patents are obtained, allowing for the sequential analysis of detailed indicators of inter-cluster and intra-cluster patents using Social Network Analysis (SNA), such as patent classification, identification of patent community structures, and identification of important patents within patent clusters. This research employs a generic analytical approach to collect, analyze, and explore global ICT industry patents and technologies, providing information on current trends in technology development in the field, domestic patent layouts, and global R&D focus differences. This information aids in integrating R&D resources, rationalizing investment allocations, and providing an overview of ICT industry-related circular economy net-zero technologies through ontology visualization.

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