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  • 學位論文

以創新構思問題解決方法(TRIZ)進行專利檢索之研究探討-以LCD產業為例

A Study of TRIZ for Patent Mapping-A Case Study for LCD Industries

指導教授 : 葉繼豪
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摘要


在現代知識經濟時代中,「專利」於各種各類知識當中是最具經濟價值也可具體評量。於是蘇俄工程師兼發明家Genrich Altshuller與他的團隊於從事專利文件分析並發展而成的一套創新構思問題解決方法(TRIZ)。近年來,TRIZ與專利之間的新興研究逐漸受到注目,如透過文字探勘(TM)技術運用,可克服現行國際專利分類方法(IPC)的限制,產生一個專屬於TRIZ快速關聯導向之專利檢索方式;除此之外,由TRIZ之父G. Altshuller所提出的40個創新原則,有學者提出評論其有部份原則過於抽象不易理解、原則間部份重疊(overlapped)等情況,並以分析與合併方式使創新原則更方便使用。而在過去的TRIZ創新原則之自動專利分類研究中,專利實驗樣本皆過於發散且無聚焦於特定產業上,產生之效益有限。有鑑於此,本論文專利實驗樣本將聚焦於LCD相關產業中華民國專利,進行TRIZ自動專利分類之研究,共收集LCD產業1000筆中華民國專利,並以三種創新原則組合做為專利分類準則,分別為:G. Altshuller所提出40個創新原則類別、H. Cong的22個創新原則群組類別與K. Rantanen的13個創新原則群組類別;並藉由一連續的文字探勘步驟與以支援向量機(SVM)與最近鄰居法(KNN)為分類器,進行實驗並評估分類結果績效(準確率、精準度、回想率與F(2)-value)。由本論文實驗中得到結論,TRIZ創新原則合併並不能提升整體分類效果,有可能將原本分類結果不佳之類別更加惡化,增加分類之複雜度;SVM與KNN皆有不錯分類效果,兩者準確率差不超過2%;本論文針對LCD產業專利進TRIZ創新原則專利分類,雖然顯示僅有65.5%之分類效果,但分類結果足以提供LCD產業研發創新者在使用TRIZ上作為觸類旁通之用。

並列摘要


The father of innovative problem-solving methods (TRIZ), Genrich Altshuller and his team engaged in patent documents and developed innovative TRIZ. The 40 TRIZ innovative principles had been considered as most popular and fastest to implement in TRIZ applications. Some scholars announced that some innovative principles were overlapped and ambiguous. They tried to cluster innovative principles into certain groups for more feasible in automatic patent classification. It has limited effectiveness for TRIZ users in a specific industry. The aim of this research is to classify 1,000 Chinese patents of ROC LCD-related industry into TRIZ innovative principles by using text mining techniques. The 1,000 patents have been mapping into alternative TRIZ innovative principles grouping approaches (40 innovative principles by G. Altshuller, 22 categories of innovative principles by H. Cong, and 13 categories of innovative principles by K. Rantanen), respectively. First of all, using on-line auto-tag system provided by Academia Sinica to break every sentence in a document into several keywords and label these keywords manually. Calculating text frequency (TF) and inverse document frequency (IDF) in the corresponding documents. Secondly, chi-square statistics and correlation coefficient approaches are used to select and sort word features highly correlated to TRIZ innovative principles. Then, TFIDF and weight-TFIDF values for selected keywords are calculated and further incorporated with classifiers such as Support Vector Machines (SVM) and K-Nearest neighbor classifier (KNN). Finally, SVM and KNN evaluate the performances of 1,000 Chinese R.O.C patents of LCD-related industry with respect to 3 TRIZ innovative principles grouping approaches as mentioned. As far as Chinese patents concerned, experimental results show that 40 TRIZ innovative principles merging into certain groups may not be enhance the efficiency of patent classification. Clustering TRIZ innovative principles into certain groups incur poor result and increase the complexity of classification. Both of SVM and KNN perform well and the accuracy between SVM and KNN was less than 2%. However, the best result of classification only had 65.5%. Even though, the result of Chinese patent classification into TRIZ innovative principles could encourage LCD industry to generate new and feasible ideas.

參考文獻


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被引用紀錄


林瑞庭(2011)。萃智(TRIZ)創新高關聯專利檢索與網路平台建置—以中華民國專利與美國專利為例〔碩士論文,國立臺北科技大學〕。華藝線上圖書館。https://doi.org/10.6841/NTUT.2011.00043
游子鋐(2009)。以創新構思問題解決方法(TRIZ)進行關聯專利檢索之研究探討-以綠色產業為例〔碩士論文,國立臺北科技大學〕。華藝線上圖書館。https://doi.org/10.6841/NTUT.2009.00468

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