臺灣博碩士論文加值系統

生活於數位時代，巨量的個人生命記憶使得人們難以輕易解讀，必須經過檢索或標籤化才可以進一步瞭解背後的意涵。本研究著力個人記憶裡繁瑣及週期性的廣泛事件，進行於「情節記憶語意化」以及「何以權衡大眾與個人資訊」兩議題之探討。透過生命記憶平台裡影像標籤自動化功能，我們以時空資訊為索引提出持續性概念重構模型，整合共同知識、個人近況以及個人偏好三項因素，模擬人們對每張照片下標籤時的認知歷程，改善其廣泛事件上註釋困難。在實驗設計上，實作大眾資訊模型、個人資訊模型以及本研究持續性概念重構模型，並招收九位受試者來剖析其認知歷程以及註釋效率。實驗結果顯示持續性概念重構模型解決了上述大眾與個人兩模型上的極限，即舊地重遊、季節性活動、非延續性活動性質以及資訊邊界註釋上的問題，因此本研究達成其個人生命記憶在廣泛事件之語意標籤自動化示範。

In the digital era, labeling and retrieving are ways to understand the meaning behind a huge amount of lifetime archive. Foucusing on tedious and periodic general events, this study will discuss two issues: (1) the semantics of episodic memory (2) the trade-off between common and personal knowledge. Using the automatic image-tagging technique of lifelong digital archiving system, we propose the Coutinuous Reconceptualization Model which models the cognitive processing of examplar categorization based on temporal-spatial information. Integrating the common knowlegde, current personal life and hobby, the Continuous Reconceptualization Model improves the tagging efficiency. In this experiment, we compare the accuracy of cognitive modeling and tagging efficiency of the three distinct models: the common knowledge model, personal knowledge model and Coutinuous Reconceptualization Model. Nine participants were recruited to label the photos. The results show that the Continous Reconceptualization Model overcomes the limitations inherent in other models, including the auto-tagging problems of modeling certain situations, such as re-visiting places, seasonal activities, noncontinuous activities and information boundary. Consequently, the Continuous Reconceptualization Model demonstrated the efficiency of the automatic image-tagging technique used in the semantic labeling of the general event of personal memory.

第一章 緒論 1
1.1 研究背景與動機 1
1.2 研究問題與目的 2
1.3 論文結構 5
第二章 生命記憶之文獻回顧 6
2.1 長期記憶及其特性 7
2.1.1 長期記憶 7
2.1.2 脈絡、長期記憶與自傳性記憶 9
2.1.3 小結 14
2.2 記憶數位化 15
2.2.1 個人生命典藏 15
2.2.2 從記憶朝向回憶 17
2.2.3 生命記憶之數位模擬與應用 18
2.2.4 小結 21
2.3 影像標籤自動化 22
2.3.1 記憶的表達 22
2.3.2 影像記憶與檢索 23
2.3.3 以廣泛或個人知識之描述標籤推薦 25
2.3.4 小結 26
2.4 總結 27
第三章 持續性概念重構個人化影像標籤系統 29
3.1 基於空間與時間知識本體 29
3.2 持續性概念重構模型 32
3.3 系統架構 37
3.4 系統功能與介面 38
第四章 實驗與評估 40
4.1 實驗模型說明 40
4.2 實驗環境 41
4.3 受試者與指導語 41
4.4 評估方式 42
第五章 結果與討論 44
5.1 基本資訊 44
5.2 認知歷程評估 45
5.3 標籤註釋效率的評估 49
5.4 跨事件之間標籤相似性評估 51
5.5 時間與地理相依性標籤相似性評估 53
5.5 綜合討論 53
第六章 結論與展望 56
參考文獻 58
附錄1 系統介面 63
附錄2 地理相依性效率統計表 66
附錄3 時間相依性效率統計表 70
附錄4 地理相依性標籤相似性詳細表格 77
附錄5 時間相依性標籤相似性詳細表格 82
附錄6 時間與地理相依性標籤相似性詳細表格 91

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