本研究試圖從心理學出發，探究描述情緒狀態的分類方法為何， 為了進行情緒與語意的連結，我們試圖將影像當作情緒狀態的刺激 來源，針對Flickr網路社群所共建共享的內容進行抽樣與觀察，使 用心理學研究中基礎的情緒字詞與詞性變化，提取12,000張帶有字 詞標籤的照片，進行標籤字詞與情緒分類字詞共現的計算、關聯規則 計算。同時，透過語意差異量表，提出了新的偏向與強度的座標分類 方法。 透過頻率門檻的過濾、詞性加註與詞幹合併字詞的方法，從 65983個不重複的文字標籤中，最後得到272個帶有情緒偏向的事物 概念字詞，以及正負偏向的情緒關聯規則。為了透過影像驗證這些字 詞是否與影像內容帶給人們的情緒狀態有關聯，我們透過三種查詢 管道：Flickr單詞查詢、google image單詞查詢、以及我們透過照片 標籤綜合指標：情緒字詞比例、社群過濾參數來選定最後要比較的 42張照片。透過語意差異量表，測量三組照片在136位使用者的答案 中，是否能吻合先前提出的強度-偏向模型。 實驗結果發現，我們的方法和google image回傳的結果類似， 使用者問卷調查結果支持我們的方法對於正負偏向的判定，且比 google有更佳的強弱分離程度。 / This study attempts to proceed from psychology to explore the emotional state of the classification method described why, in order to be emotional and semantic links, images as we try to stimulate the emotional state of the source, the Internet community for sharing Flickr content sampling and observation, using basic psychological research in terms of mood changes with the parts of speech, with word labels extracted 12,000 photos, label and classification of words and word co-occurrence of emotional computing, computing association rules. At the same time, through the semantic differential scale, tend to put forward a new classification of the coordinates and intensity. Through the frequency threshold filter, filling part of speech combined with the terms of the method stems from the 65,983 non-duplicate text labels, the last 272 to get things with the concept of emotional bias term, and positive and negative emotions tend to association rules. In order to verify these words through images is to bring people's emotional state associated with our pipeline through the three sources: Flickr , google image , and photos through our index labels: the proportion of emotional words, the community filtering parameters to select the final 42 photos to compare. Through the semantic differential scale, measuring three photos in 136 users of answers, whether the agreement made earlier strength - bias model. Experimental results showed that our methods and google image similar to the results returned, the user survey results support our approach to determine the positive and negative bias, and the strength of better than google degree of separation.

偵測新興議題對於研究者而言是一個相當重要的問題，研究者如何在有限的時間和資源下探討同一領域內的新興議題將比解決已經成熟的議題帶來較大的貢獻和影響力。本研究將致力於協助研究者偵測新興且具有未來潛力的研究議題，並且從學術論文中探究對於研究者在做研究中有幫助的學術智慧。在搜尋可能具有研究潛力的議題時，我們假設具有研究潛力的議題將會由同一領域中較具有影響力的作者和刊物發表出，因此本研究使用貝式估計的方法去推估同一領域中相關的研究者和學術刊物對於該領域的影響力，進而藉由這些資訊可以找出未來具有潛力的新興候選議題。此外就我們所知的議題偵測文獻中對於認定一個議題是否已經趨於成熟或者是否新穎且具有研究的潛力仍然缺乏有效及普遍使用的衡量工具，因此本研究試圖去發展有效的衡量工具以評估議題就本身的發展生命週期是否仍然具有繼續投入的學術價值。 本研究從許多重要的資料庫中挑選了和資料探勘和資訊檢索相關的論文並且驗證這些在會議論文中所涵蓋的議題將會領導後續幾年期刊論文相似的議題。此外本研究也使用了一些已經存在的演算法並且結合這些演算法發展一個檢測的流程幫助研究者去偵測學術論文中的領導趨勢並發掘學術智慧。本研究使用貝式估計的方法試圖從已經發表的資訊和被引用的資訊來建構估計作者和刊物的影響力的事前機率與概似函數，並且計算出同一領域重要的作者和刊物的影響力，當這些作者和刊物的論文發表時將會相對的具有被觀察的價值，進而檢定這些新興候選議題是否會成為新興議題。而找出的重要研究議題雖然已經縮小探索的範圍，但是仍然有可能是發展成熟的議題使得具有影響力的作者和刊物都必須討論，因此需要評估議題未來潛力的指標或工具。然而目前文獻中對於評估議題成熟的方法僅著重在議題的出現頻率而忽視了議題的新穎度也是重要的指標，另一方面也有只為了找出新議題並沒有顧及這個議題是否具有未來的潛力。更重要的是單一的使用出現頻率的曲線只能在議題已經成熟之後才能確定這是一個重要的議題，使得這種方法成為落後的指標。 本研究試圖提出解決這些困境的指標進而發展成衡量新興議題潛力的方法。這些指標包含了新穎度指標、發表量指標和偵測點指標，藉由這些指標和曲線可以在新興議題的偵測中提供更多前導性的資訊幫助研究者去建構各自領域中新興議題的偵測標準。偵測點所代表的意義並非這個議題開始新興的正確日期，它代表了這個議題在自己發展的生命週期上最具有研究的潛力和價值的時間點，因此偵測點會根據後來的蓬勃發展而在時間上產生遞延的結果，這表示我們的指標可以偵測出議題生命力的延續。相對於傳統的次數分配曲線可以看出議題的崛起和衰退，本研究的發表量指標更能以生命週期的概念去看出議題在各個時間點的發展潛力。本研究希望從這些過程中所發現的學術智慧可以幫助研究者建構各自領域的議題偵測標準，節省大量人力與時間於探究新興議題。本研究所提出的新方法不僅可以解決影響因子這個指標的缺點，此外還可以使用作者和刊物的影響力去針對一個尚未累積任何索引次數的論文進行潛力偵測，解決Google 學術搜尋目前總是在論文已經被很多檢索之後才能確定論文重要性的缺點，學者總是希望能夠領先發現重要的議題或論文。然而，我們以議題為導向的檢索方法相信可以更確實的滿足研究者在搜尋議題或論文上的需求。 / This research presents endeavors that seek to identify the emerging topics for researchers and pinpoint research intelligence via academic papers. It is intended to reveal the connection between topics investigated by conference papers and journal papers which can help the research decrease the plenty of time and effort to detect all the academic papers. In order to detect the emerging research topics the study uses the Bayesian estimation approach to estimate the impact of the authors and publications may have on a topic and to discover candidate emerging topics by the combination of the impact authors and publications. Finally the research also develops the measurement tools which could assess the research potential of these topics to find the emerging topics. This research selected huge of papers in data mining and information retrieval from well-known databases and showed that the topics covered by conference papers in a year often leads to similar topics covered by journal papers in the subsequent year and vice versa. This study also uses some existing algorithms and combination of these algorithms to propose a new detective procedure for the researchers to detect the new trend and get the academic intelligence from conferences and journals. The research uses the Bayesian estimation approach and citation analysis methods to construct the prior distribution and likelihood function of the authors and publications in a topic. Because the topics published by these authors and publications will get more attention and valuable than others. Researchers can assess the potential of these candidate emerging topics. Although the topics we recommend decrease the range of the searching space, these topics may so popular that even all of the impact authors and publications discuss it. The measurement tools or indices are need. But the current methods only focus on the frequency of subjects, and ignore the novelty of subjects which is critical and beyond the frequency study or only focus one of them and without considering the potential of the topics. Some of them only use the curve of published frequency will make the index as a backward one. This research tackles the inadequacy to propose a set of new indices of novelty for emerging topic detection. They are the novelty index (NI) and the published volume index (PVI). These indices are then utilized to determine the detection point (DP) of emerging topics. The detection point (DP) is not the real time which the topic starts to be emerging, but it represents the topic have the highest potential no matter in novelty or hotness for research in its life cycle. Different from the absolute frequent method which can really find the exact emerging period of the topic, the PVI uses the accumulative relative frequency and tries to detect the research potential timing of its life cycle. Following the detection points, the intersection decides the worthiness of a new topic. Readers following the algorithms presented this thesis will be able to decide the novelty and life span of an emerging topic in their field. The novel methods we proposed can improve the limitations of impact factor proposed by ISI. Besides, it uses the impact power of the authors and the publication in a topic to measure the impact power of a paper before it really has been an impact paper can solve the limitations of Google scholar’s approach. We suggest that the topic oriented thinking of our methods can really help the researchers to solve their problems of searching the valuable topics.

在二十一世紀中， LED發光二極體更是備受期待的節能產品。過去背光源一直是LED主要應用項目，而漸漸地照明也開始採用LED產品，甚至各國已宣布將禁用白熾燈。然而，在各國政府及業者大力推廣及投入LED產業之際，目前LED產品尚未能實現市場替代效應之事實卻不容忽視。細究其可能原因，是否LED產品仍有技術功能缺陷，抑或其價格無法競爭，又者消費者對產品認知不足、終端通路尚未成熟、品牌塑造尚待建立等因素，讓消費者暫時裹足不前? 鑒於台灣在LED產業中已有完整的上中下游布局，不但是下游封裝的全球最大供應中心，近年更也逐步紮根中游晶粒產品，甚至切入上游單晶基板、磊晶產品製程。故此，本研究希冀探查現有LED產品所遭遇之困難，以功能品質及經濟價值等角度，找尋可突破市場瓶頸之關鍵因素，並針對其中可進行專利檢索及分析的較具技術性因素：LED單晶基板，以中國大陸此成長最為顯著之市場作為專利檢索及分析之核心地理區域，探討LED單晶片基板之專利發展趨勢以及研發參考目標及方向。 在進行專利檢索之前，本研究將先行剖析現有LED單晶片基板的應有功能、重點特性、4大類基板材料選擇與其最新研發優勢，包含藍寶石、碳化矽、矽、氮化鎵，以助於後續專利檢索及分析結果之觀察思考。本研究的結論與建議將分別針對不同的LED單晶片基板材料選擇，以專利分析結果對照其市場發展近況，向台灣業者提出藍寶石、碳化矽已係過度競爭、不宜進入的項目，並在最後建議台灣業者仍可持續投入研發LED矽、氮化鎵基板材料，以及額外以技術與應用創新增加其產品的市場連結度及應用產業競爭利基。 / Nowadays LED has become a future mainstream of highly expected energy-saving product. Back-lighting has been the main application for LED, such as in monitors, and furthermore lighting has grown its market size into significance. However, it should draw attention that LED products has not yet fully replace conventional lighting as expected, due to a number of possible factors, including functions, prices, consumer awareness, channeling, and/or branding. In light of the fully established LED industry in Taiwan, including the largest downstream packaging supply source, mature middle-stream wafer production and leading upstream epitaxy and substrate manufacturing, this study aims to seek and find the patent searchable and analyzable part of the current LED obstacles in product quality and economic value perspective. As a result, single crystal substrate falls into abovementioned criteria, including four major substrate materials: sapphire, silicon carbonate, silicon, and gallium nitrite. This study further concentrates the patent search and analysis on China, the fastest growing LED market among all regions and the biggest opportunity for Taiwan players. Before patent search, this study gives a detailed elucidation about four substrate materials on functions, important traits, different types and respective R&D updates and breakthrough, followed by interpretation of and association with patent search and analysis. At the end of this study, conclusions and suggestions are given, based on Taiwan players’ current relative strength and weakness. In sum, sapphire substrates and silicon carbonate substrate have overly competitive patent and market situation, and silicon substrates and gallium nitrite substrate may allow Taiwan players to continue and/or reinforce R&D investment. Additionally, technology and application innovation could increase product-market linkage and competitive edge in LED application industry.