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研究生: 洪國恩
Guo-En Hong
論文名稱: 結合修正式DEMATEL與改良式餘弦相似度及專利類別歸屬之機率方法進行LED自行車車燈相關專利分析研究
A study of patent analysis of LED bicycle light by combining modified DEMATEL with improved cosine similarity and probability method of patent categorization
指導教授: 林榮慶
Zone-Ching Lin
口試委員: 許覺良
Chaug-liang Hsu
王國雄
Kuo-shong Wang
成維華
Wei-hua Chieng
學位類別: 碩士
Master
系所名稱: 工程學院 - 機械工程系
Department of Mechanical Engineering
論文出版年: 2015
畢業學年度: 103
語文別: 中文
論文頁數: 198
中文關鍵詞: LED閱讀燈sLED自行車車燈sDEMATELslife span餘弦相似度機率專利分析
外文關鍵詞: LED reading lamp, LED bicycle light, DEMATEL, life span, cosine similarity, probability, patent analysis
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  • 本研究首先提出修正式DEMATEL經由常態化數值的概念來評估技術領域間0~4的相互影響程度,用以取代傳統的專家問卷方式。本研究先以LED閱讀燈為例,初步分類為七個重要技術領域,透過每個技術領域所具有的相關技術字以及常態化值,先計算技術領域間重複或定義相同的技術字常態化值,再計算技術領域間常態化值佔有之比例,並依照所計算出的比例值,來評估決定技術領域間的相互影響程度0~4之值。接著再依照DEMATEL運算步驟求出總關係影響矩陣、直接/間接關係圖及(D+R)值與(D-R)值之因果圖。此(D+R)值與(D-R)值之因果圖可協助判斷技術領域間的相互受影響程度以及哪些技術領域屬於較為核心技術領域的判定。
    本研究首先以現有LED閱讀燈3篇相關專利測試,將DEMATEL繪製出的不同技術領域的因果圖,並計算各技術領域的機率值,進而判斷新投入專利是否具有一個以上的技術領域。然後再以LED自行車車燈為研究之載具,並建立各第一層及第二層技術類別及功能類別之技術字字群及功能字字群。本文經由專利語意分析之斷詞斷字系統半自動半人工分析所獲得之各關鍵技術字、零組件元件字及功能字之常態化數值做為該詞彙之權重,以結合改良式餘弦相似度概念之創新專利搜尋方法搜尋相關專利,及以改良式餘弦相似度結合專利類別歸屬之機率方法進行專利歸屬之計算。本文並進行3篇LED自行車車燈之新投入專利之專利歸屬判別,計算專利歸屬之機率值(Pj值),若是新投入專利之技術領域的機率值沒有太大差異,且技術領域之因果關係為相關,在人工判定時特別注意,最後判定新投入專利是否具有一個以上的技術領域。
    本文LED自行車車燈亦進行專利之國際專利分類(IPC)分析及以技術領域為主之專利分析。另亦增加專利生命跨距(Life Span)的分析,其以專利公告日為依據,統計並製作出專利生命跨距(Life Span)。經由專利生命跨距(Life Span)分析,可看出跨距長的技術領域的技術領域相關專利可能已發展成熟,跨距短的技術領域之專利表示該技術領域之相關專利有較大的發展空間,有投資研發的潛力。


    The study proposes a modified DEMATEL that evaluates the mutual influence among 0~4 scales by using the concept of normalized numerical value to replace the conventional collecting experts’ opinions through questionnaires. First of all, the study takes LED reading lamp for example, and preliminarily classifies its techniques into 7 most important technical categories. Through the related technical words that each technical category has and their normalized numerical values, the study firstly calculates the normalized numerical values of repeated technical words among the technical fields or those having the same definitions. Then the study calculates the ratios of the normalized values among the technical categories. Based on the ratios calculated, the study assesses the determined mutual influence scales 0~4 among the technical categories. After that, following the calculation procedures of DEMATEL, the study finds out the general relational influence matrix, direct/indirect relationship diagram, and the cause and effect diagram between (D+R) value and (D-R) value. The cause and effect diagram between (D+R) value and (D-R) value can help judge the degree of mutual influence among the technical categories, and judge which technical categories belong to more core technical categories.
    First of all, the study uses 3 patents of LED reading lamp as the new added testing patents to draw a cause and effect diagram of different technical categories by DEMATEL. Finally, the study calculates the probability value of each technical category and judges whether the newly added patent has more than one technical category. Then, taking LED bicycle light as the carrier, the study produces the 1st layer and 2nd layer technical/functional matrices, and establishes the technical word cluster and functional word cluster for each of the 1st layer and 2nd layer technical categories and functional categories. The normalized numerical values of the various key technical words, part/component words and functional words, which are obtained from semi-automatic and semi-manual analysis of term and word segmentation system of patent semantic analysis, are taken as the weights of the vocabularies. The study combines with the innovative patent search method of improved cosine similarity concept to search the related patents, and calculates the category of patent by combining improved cosine similarity with probability method of patent categorization. The paper judges the category of the newly added patent for 3 patents of LED bicycle light, and calculates the probability value (Pj value) of patent categorization. If there is not a great difference in the probability values for the technical categories of the newly added patent, and the cause and effect relationship between technical categories is correlated, then special attention has to be paid during manual judgment. Finally, it is judged whether the newly added patent has more than one technical category.
    The study’s LED bicycle light also adopts IPC (International Patent Classification) analysis of patent, and makes patent analysis that mainly focuses on technical category. Besides, the study adds an analysis on life span of patent. With the announcing date of patent as the basis, the study makes statistics and estimates the life span of patent. As seen from the analysis on life span of patent, the technical category-related patent with technical category having a long life span may have been developed maturely. As to technical category having a short life span, such technical category-related patent has broader development and greater potential for R&D investment.

    摘要 I Abstract III 誌謝 VI 目錄 VII 圖目錄 XII 表目錄 XIV 第一章 緒論 1 1.1 研究背景 1 1.2研究動機與目的 2 1.3 文獻回顧 2 1.4 論文架構 7 第二章 LED自行車車燈介紹 12 2.1 LED發光原理與結構介紹 12 2.2 LED自行車車燈 15 2.3 LED自行車車燈物料表(BOM) 16 第三章 建立繁體、簡體中文及英文之斷詞斷字系統 20 3.1 繁體、簡體中文零組件元件字斷詞點 20 3.2 英文零組件元件字斷詞點 24 3.3 技術詞句之第一層及第二層斷詞點 26 3.4 功能詞句之斷詞點 29 第四章 改良式餘弦相似度概念進行專利搜尋與專利分析並結合專利類別歸屬之機率方法進行專利歸屬 32 4.1 專利各關鍵字計算之常態化數值之概念及說明 32 4.2 餘弦相似度簡介 33 4.3 改良式餘弦相似度介紹說明 34 4.4 結合改良式餘弦相似度之專利搜尋及歸納方法 38 4.5 結合改良式餘弦相似度之初步專利分析歸類 41 4.6 結合改良式餘弦相似度及專利類別歸屬之機率方法進行專利歸屬 41 第五章 結合修正式DEMATEL與改良式餘弦相似度及專利類別歸屬之機率方法,進行專利歸屬判定 45 5.1 決策實驗室分析法(Decision-Making Trial and Evaluation Laboratory,DEMATEL) 45 5.2 修正式決策實驗室分析法 50 第六章 以LED閱讀燈相關專利做為測試結合修正式DEMATEL與改良式餘弦相似度進行專利歸屬判定 52 6.1 LED閱讀燈相關專利之第一層及第二層技術類別及功能類別之技術字及功能字字群與技術/功能矩陣歸納結果 52 6.2 依修正式DEMATEL建立直接關係矩陣與計算直接/間接關係矩陣繪製LED閱讀燈因果圖 57 6.3 以LED閱讀燈相關專利測試於改良式餘弦相似度結合專利類別歸屬之機率方法模糊值設定 74 6.4 結合修正式DEMATEL與改良式餘弦相似度及專利類別歸屬之機率方法進行LED閱讀燈相關專利判定 76 6.4.1 以專利號M434892為例,結合修正式DEMATEL與改良式餘弦相似度及專利類別歸屬之機率方法進行LED閱讀燈相關專利判定之結果 76 6.4.2 以專利號M383675為例,結合修正式DEMATEL與改良式餘弦相似度及專利類別歸屬之機率方法進行LED閱讀燈相關專利判定之結果 79 6.4.3 以專利號CN102022648為例,結合修正式DEMATEL與改良式餘弦相似度及專利類別歸屬之機率方法進行LED閱讀燈相關專利判定之結果 86 第七章 以改良式餘弦相似度概念進行LED自行車車燈專利搜尋 93 7.1 結合改良式餘弦相似度對LED自行車車燈之專利搜尋及歸納其相關專利 93 7.2 建立LED自行車車燈相關專利重要關鍵字之初步繁體、簡體及英文同義字對照表 104 第八章 結合修正式DEMATEL與改良式餘弦相似度及專利類別歸屬之機率方法進行LED自行車車燈專利歸屬之判定 105 8.1 初步建立LED自行車車燈相關專利之第一層及第二層技術/功能矩陣 105 8.2 分析歸納LED自行車車燈相關專利之第一層及第二層技術類別及功能類別之技術字及功能字字群並建立相關專利之第一層及第二層技術/功能矩陣 106 8.3 建立LED自行車車燈相關專利重要關鍵字之完整繁體、簡體中文及英文同義字對照表 111 8.4 依修正式DEMATEL建立直接關係矩陣與計算直接/間接關係矩陣繪製LED自行車車燈因果圖 112 8.5 結合修正式DEMATEL與改良式餘弦相似度及專利類別歸屬之機率方法進行LED自行車車燈相關專利判定 119 8.5.1 以專利號US20020093825A1為例,結合修正式DEMATEL與改良式餘弦相似度及專利類別歸屬之機率方法進行LED自行車車燈相關專利判定之結果 120 8.5.2 以專利號US20080002416A1為例,結合修正式DEMATEL與改良式餘弦相似度及專利類別歸屬之機率方法進行LED自行車車燈相關專利判定之結果 126 8.5.3 以專利號M475398為例,結合修正式DEMATEL與改良式餘弦相似度及專利類別歸屬之機率方法進行LED自行車車燈相關專利判定之結果 132 第九章 建立LED自行車車燈相關專利分析之結果與專利生命跨距(life span)討論 139 9.1 建立LED自行車車燈相關專利分析之結果與討論 139 9.2 LED自行車車燈相關專利之IPC分析、所屬國別分析、申請人分析及公司別分析 139 9.3 LED自行車車燈各第一層及第二層技術類別與公司別分析、競爭者IPC技術核心分布分析、競爭者研發活動力趨勢分析及技術層活動力趨勢分析 148 9.4 LED自行車車燈專利生命跨距(life span) 158 第十章 結論 162 參考文獻 163 附錄A_LED自行車車燈相關之中英文專利之第一層及第二層技術/功能矩陣及相關專利 167

    【1】 「國際專利分類表第七版使用指南」,經濟部智慧財產局,民國九十年。
    【2】 「國際專利分類之研究」,經濟部中央標準局。
    【3】 Overview of the Classification System, http://www.uspto.gov/main/patents.htm
    美國專利商標(USPTO)。
    【4】 The EPO guide to patent information on the internet,http://epart.epo.org/dwl/espacenet_manual.pdf
    歐洲專利組織(EPO)。
    【5】 Trappey, C.V., Trappey, A.J.C., and Wu, C.Y., “Clustering patents using non-exhaustive overlaps”, Journal of Systems Science and Systems Engineering, Vol.19, No.2, pp.162-181 (2010).
    【6】 Trappey, C.V., Trappey, A.J.C., and Wu, C.Y., “Automatic patent document summarization for collaborative knowledge systems and services”, Journal of Systems Science and Systems Engineering, Vol.18, No.1, pp.71-94 (2009).
    【7】 Singhal, A. and Salton, G., “Automatic Text Browsing Using Vector Space Model”, Technical Report, Department of Computer Science, Cornell University, (1993).
    【8】 Lawrence, S. and Giles, C.L., “Searching the Web : General and Scientific Information Access”, IEEE Communication, Vol.37, pp.116-122 (1999).
    【9】 陳哲宏、陳逸南、謝銘洋、徐宏昇,「專利法解讀」,月旦出版公司,第14-15頁,民國八十三年。
    【10】 Gruber, T., “A translation approach to portable ontology specifications”, Knowledge Acquisition, Vol.5, pp.199-200 (1993).
    【11】 O’Leary, D.E., “Enterprise knowledge management”, IEEE Computer, Vol.31, pp.54-61 (1998).
    【12】 杜家宏,「整合繁體和簡體中文及英文斷詞斷字系統之發光二極體檯燈專利分析研究」,碩士論文,國立台灣科技大學機械工程學系,台北,民國一百年。
    【13】 吳俞灃,「LED水族燈之相關專利分析研究」,碩士論文,國立台灣科技大學機械工程學系,台北,民國一百零一年。
    【14】 Salton, G. and McGill, M., “Introduction to Modern Information Retrieval”, McGraw-Hill, New York, (1983).
    【15】 Vallet, D., Fernández, M. and Castells, P., “An Adaptation of the Vector-Space Model for Ontology-Based Information Retrieval”, IEEE Knowledge and Data Engineering, Vol.19, No.2, pp.261-272 (2005).
    【16】 Wang, S., Sun, J., Gao, B.J. and Ma, J., “Adapting Vector Space Model to Ranking-based Collaborative Filtering”, CIKM '12 Proceedings of the 21st ACM international conference on Information and knowledge management, pp.1487-1491, New York, USA (2012).
    【17】 Gan, J. and Chen, L.C., “Research of improved IF-IDF Weighting algorithm”, International Conference on Information Science and Engineering (ICISE), pp.2304-2307, Hangzhou, China (2010).
    【18】 Zhang, G.H. and Odbal, “Sentence Alignment For Web Page Text Based On Vector Space Model”, International Conference on Computer Science and Information Processing (CSIP), pp.167-170, Shaanxi, China (2012).
    【19】 Trappey, C.V., Wang, T.M., Hoang, S. and Trappey, A.J.C., “Constructing a dental implant ontology for domain specific clustering and life span analysis,” Advanced Engineering Informatics Vol.27, p.p.346-357 (2013).
    【20】 Bermudez-Edo, M., Noguera, M., Hurtado-Torres, N., Hurtado, M.V. and Garrido, J.L., “Analyzing a firm’s international portfolio of technological knowledge: A declarative ontology-based OWL approach for patent documents,” Advanced Engineering Informatics Vol.27, p.p.358-365 (2013).
    【21】 Trappey, C.V., Trappey, A.J.C., Peng, H.Y., Lin, L.D. and Wang, T.M., “A knowledge centric methodology for dental implant technology assessment using ontology based patent analysis and clinical meta-analysis,” Advanced Engineering Informatics Vol.28, p.p153-165 (2014).
    【22】 Cao, H., and Jia, H., ‘‘Tibetan text classification based on the feature of position weight”, 2013 International Conference on Asian Language Processing (IALP), p.p.220-223, Urumqi, Xinjiang, China (2013).
    【23】 LED inside of TRENDFORCE Corp., http://www.ledinside.com.tw/knowledge/20120801-22324.html
    【24】 林武憲,「LED整合中英文斷詞斷字系統之專利分析」,碩士論文,國立台灣科技大學機械工程學系,台北,民國九十九年。
    【25】 McGlen, R.J., Jachuck, R., and Lin, S., “Integrated Thermal Management Techniques for High Power Electronic Devices”, Applied Thermal Engineering, Vol.24, Issue 8-9, pp.1143-1156 (2004).
    【26】 Altuntas, S. and Dereli, T., ‘‘A novel approach based on DEMATEL method and patent citation analysis for prioritizing a portfolio of investment projects’’, Expert systems with Applications, Vol.42, p.p.1003-1012 (2015).
    【27】 Han, W.M., Hsu, C.H. and Yeh, C.Y., “Using DEMATEL to Analyze the Quality Characteristics of Mobile Applications.” Proceedings of the 2014 International Conference on Future Information Engineering and Manufacturing Science, p.p.131-134 (2014).

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