許永真臺灣大學:資訊工程學研究所陳麗徽Chen, Li-HuiLi-HuiChen2010-05-182018-07-052010-05-182018-07-052008U0001-2608200816473000http://ntur.lib.ntu.edu.tw//handle/246246/183605儘管電腦科學已有了相當長遠的發展，還是存在著一些問題是人們可以輕易解決，但是電腦卻沒有辦法的，像是圖片辨識(image recognition)和圖片標註(image annotation)。而人力計算(human computation)是專門在研究這類問題的一個新的研究領域，本篇論文即是利用人力計算的方法，讓人們來幫助解決這些電腦沒有辦法有效解決的問題。這裡我們提出了一個兩人網路線上遊戲Image Hunter來幫助完成網路上建築地標圖片的標註(landmark image annotation)。除此之外，我們著重在分析遊戲中收集到的資料的品質分析。我們提出信任值估算(confidence evaluation)的方法取代了次數累積(times accumulation)的方法來評估資料收集的正確性。我們請來了28位受測者來進行實驗，實驗結果驗證了遊戲機制的合理性，以及信任值估算的方法可以有效地提升收集到的資料的正確性。Despite impressive advancement in computer technology, there are still some problems that humans can solve efficiently but current computer programs can not. Image recognition and annotation are examples. Human computation is a new research area that focuses on this kind of problems. This thesis aims to explore the power of human computation and shows how humans could help solve problems that are hard for computers. We propose a two-player online human computation game, Image Hunter, to achieve the task of annotating for a collection of landmark images on the Internet. Moreover, we address on the quality analysis for the data collected by the game. We propose confidence evaluation instead of times accumulation to estimate the accuracy of the data. Experiments involving 28 players have been conducted. The preliminary results demonstrate that the game mechanism is reasonable and with confidence evaluation mechanism the accuracy improves effectively.Acknowledgments iiibstract vist of Figures xiist of Tables xiiihapter 1 Introduction 1.1 Background 1.2 Research Objectives 2.3 Thesis Structure 3hapter 2 Related Work 5.1 Collaborative Information Repositories 5.2 Human Computation 6.2.1 The ESP Game and Peekaboom 7.2.2 Other Applications 8.3 Quality Analysis for Collaborative Information Repositories 9hapter 3 Semantic Annotation 11.1 Annotating Landmark Images on the Web with their Proper Names 12.2 Problem Definition 12.3 Proposed Solution 13.3.1 A Human Computation Game: ImageHunter 14.3.2 Confidence Evaluation 15hapter 4 Human Computation Game Design 17.1 Game Mechanism 17.1.1 Game Rules 18.1.2 Scoring Mechanism 18.2 General Design Principles of Games 21hapter 5 Confidence Evaluation 25.1 Rationality of ImageHunter 25.1.1 Candidate Images 26.1.2 Scoring Mechanism 27.2 Confidence Evaluation Mechanism 29.2.1 Confidence Measurment 30hapter 6 Experiment 35.1 Data Collection 35.2 Evaluation 36.2.1 Player’s Action 36.2.2 Confidence Measurement for Gaming Data 37.2.3 Performance among Different Mechanisms 38hapter 7 Conclusion 43.1 Summary of Contributions 43.2 Future Work 44ibliography 46application/pdf664219 bytesapplication/pdfen-USHuman Computation GamesProductivity GamesAccuracy AnalysisConfidenceConfidence Evaluation人機協力演算法具有生產力的遊戲正確性分析信任值信任值估算thesishttp://ntur.lib.ntu.edu.tw/bitstream/246246/183605/1/ntu-97-R95922054-1.pdf