臺灣博碩士論文加值系統

當專利權受到侵害時，專利權人可向侵權人要求賠償所受到的損失，因此企業若捲入專利侵權案，往往需付出龐大的時間與金錢作為代價。而隨著知識經濟時代的到來，企業間的競爭其實就是智慧財產權的競爭，先行占領未來有潛力或可能成為熱門技術領域之專利權，即可幫助企業取得未來競爭優勢。因此，專利在商場上的重要性絕對不可小覷。然而，隨著科技的快速發展以及時間的累積，專利文件的數量非常龐大。如何有效的管理龐大數量的專利文件，已是目前炙手可熱議題。
專利地圖係指將專利檢索系統所得之結果，藉由各種統計方法分析，最後以圖像化的圖表呈現結果，以方便使用者閱覽。本研究提出一個建構出專利地圖和推薦出技術缺口或技術機會的方法。建構出可區別專利相似度之專利地圖，將可幫助企業於制定研發策略時，了解技術領域分佈，避免因研發相同技術而涉入專利侵權案。推薦出技術缺口或技術機會，將可幫助企業提早評估是否需要先行占領與該技術領域相關之專利，以取得未來競爭優勢。
本研究主要的特點為在文字探勘的相關領域上，提出一個降低字詞維度的方法。在資料探勘或文字探勘的領域中，龐大數量的特徵或是字詞所形成的稀疏矩陣往往都會大幅降低整體執行的效率。因此利用本研究所提出的方法，將可降低字詞所構成的維度，達到節省儲存空間、提高檢索速度的效果。

The patentee can get the reparation for loss while the patents are infringed. If a company gets embroiled in legal disputes for patent infringement, significant losses in time and costs can occur. With the arrival of knowledge-based economy, Companies compete for the Intellectual Property Rights frequently. Occupying the patents of potential technological fields in advance will assists a company in acquiring competitive advantage in the future. As a result, patents play an important role in the marketplace. With the advance of science and technology, the amount of patent grows larger as time goes on. How to manage the considerable patents effectively is currently an important issue.
Patent map is the visualization of the results of statistical analysis applied to patent documents. This study proposes a method for constructing patent map and recommending technological vacancy. When companies are formulating research and development strategies, patent map allows them to distinguish the patent similarity and assists them in avoiding developing similar technique. The recommendation function assists companies in assessing whether to occupy technological vacancy in advance for acquiring competitive advantage in the future.
One feature of this study is the method of dimension reduction of the terms. In text mining, the sparse matrix generated by the considerable terms usually costs a lot of computational resource. Dimension reduction of the terms will save storage spaces and increase execution efficiency.

第1章 緒論 1
1.1 研究背景與動機 1
1.2 研究目的 3
1.3 研究範圍 3
1.4 研究流程 4
1.5 論文大綱 5
第2章 文獻探討 6
2.1 自然語言處理 6
2.1.1 語意網 – WordNet 6
2.1.2 詞性標記 8
2.1.3 字根還原 8
2.1.4 停用字 9
2.2 資訊檢索 9
2.3 多維尺度 11
2.4 分群演算法 13
2.4.1 分割式分群法 13
2.4.2 階層式分群法 14
2.4.3 分群效度評估 15
第3章 研究方法 17
3.1 研究架構 17
3.2 文件收集與前處理模組 19
3.3 字詞相似度計算與字詞分群模組 21
3.4 文件相似度計算模組 23
3.5 多維尺度降維模組 24
3.6 文件離群程度計算模組 25
第4章 系統建置與驗證 27
4.1 系統建置 27
4.2 實驗設計與實驗結果分析 27
4.2.1 資料集 27
4.2.2 實驗一：探討語意網對專利檢索效果之影響 28
4.2.3 實驗二：探討離群程度較高之專利文件 29
第5章 結論與未來研究方向 33
5.1 研究成果 33
5.2 未來研究方向 34

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