abstract: One of the most remarkable outcomes resulting from the evolution of the web into Web 2.0, has been the propelling of blogging into a widely adopted and globally accepted phenomenon. While the unprecedented growth of the Blogosphere has added diversity and enriched the media, it has also added complexity. To cope with the relentless expansion, many enthusiastic bloggers have embarked on voluntarily writing, tagging, labeling, and cataloguing their posts in hopes of reaching the widest possible audience. Unbeknown to them, this reaching-for-others process triggers the generation of a new kind of collective wisdom, a result of shared collaboration, and the exchange of ideas, purpose, and objectives, through the formation of associations, links, and relations. Mastering an understanding of the Blogosphere can greatly help facilitate the needs of the ever growing number of these users, as well as producers, service providers, and advertisers into facilitation of the categorization and navigation of this vast environment. This work explores a novel method to leverage the collective wisdom from the infused label space for blog search and discovery. The work demonstrates that the wisdom space can provide a most unique and desirable framework to which to discover the highly sought after background information that could aid in the building of classifiers. This work incorporates this insight into the construction of a better clustering of blogs which boosts the performance of classifiers for identifying more relevant labels for blogs, and offers a mechanism that can be incorporated into replacing spurious labels and mislabels in a multi-labeled space. / Dissertation/Thesis / Doctoral Dissertation Computer Science 2015

Ubiquitous e-service is one of the most recent links in the chain of evolution that has characterized the different eras of the internetworking environment. In this dissertation, the notion of ambient e-services is defined to identify a new scope of mobile e-services in an ubiquitous environment, addressing dynamic collective efforts between mobile users, dynamic interactions with ambient environments, the moment of value, and low cost provision. We present an ambient e-services framework characterizing three supporting stacks followed by several ambient e-service applications. We propose an ambient e-service environment that explores the promise of exploitation of the collective wisdom of proximal mobile users. In order to leap the trust barrier for the user to embracing these ubiquitous e-services, we propose an Autonomous Trust Model for exploring collective wisdom in the ubiquitous environment (hereafter termed “U-ATM”) as an instance of ASEM. ASEM (Ambient e-Service Embracing Model) addresses the core elements (of relevance to the integrated concern of trust, reputation and privacy) required for assuring such desired features as convenience, safety, fairness and collaboration for mobile users when they engage with ambient e-services. The U-ATM highlights the distributed peer-to-peer interactions under an ad-hoc network composition. It especially accommodates the dynamic short-lived identity characteristics and lightweight computational capacity of mobile devices. The U-ATM we have developed is based on the ZigBee architecture as a collaborative application in the upper layer of the ubiquitous environment. U-ATM design concepts are elaborated and evaluated. A simulation is conducted. Simulation outcomes for trust decision quality enhancement show significant improvement over traditional designs. U-ATM makes it possible for users to collaborate with the nearby user groups for establishing a reliable and trustworthy interaction environment. It also facilitates and empowers the potential benefits of various ubiquitous e-service applications.

Web 2.0時代強調由使用者貢獻內容，並藉由使用者的互動來創造群體智慧的價值。社會性書籤網站統合散佈在各處的網路資訊（尤其是由使用者所產生的部落格文章），承接內容的生產及閱讀，是網路內容價值鏈樞紐；另一方面，從媒體的角度來看，書籤網站可視為是web 2.0下的公民新聞守門人（引路人），以公民取代專業編輯，提供了一個完全不一樣的公民媒體運作方式。本研究針對社會性書籤網站中的內容評價推薦機制，探討其群體智慧運作情形：參考動物群體行為的運作原則，加上文獻的整理及實際案例的觀察，建構出社會性書籤網站推薦機制的模擬運作架構；並透過代理人模擬方法，來找出影響網站群體智慧運作的原則，及相關屬性設定對運作結果的影響。研究結果發現，社會性書籤網站的運作成效，可以分為篩選效果及文章更新效率，兩者之間具有魚與熊掌不可兼得的特性，並可藉由不同的閱讀策略安排來調整。基於web 2.0的特性，使用者同時扮演服務的生產者與消費者。因此，使用者閱讀文章時的閱讀策略安排，可視為是群體智慧運作中的工作分配策略。而群體智慧的運作原則中，正回饋效應可以提升篩選效果，判斷獨立性可以提升文章的更新效率，抑制與負回饋則可以使系統較為穩定。本研究除了為web 2.0網站的群體智慧經營提供具體的參考方針，多重代理人模擬的方法也可做為往後web 2.0相關研究及網站經營時的工具。 / The core spirit for web 2.0 is the contribution of users, and the creation of value through the interaction between users. Social book marking sites integrate all kind of contents on the Internet (especially those generated by users), and play the role of pivot between content production and consumption. From the aspect of media, social bookmarking site can be regarded as news gatekeeper (or gateway) in the web 2.0 era. This study focuses on the rating and recommendation mechanism of social bookmarking sites, trying to find out the effects of collective wisdom with regard to different operations. The principle of collective animal behavior and the existing operations of some social bookmarking sites are first surveyed. Then, an operational model of social bookmarking sites and its recommendation mechanism is built and used for subsequent simulation. / The research findings show that the performance of social bookmarking sites has a tradeoff between sifting effect and efficiency, and that the performance can be controlled through a job allocation strategy. The operation of 「positive feedback」in collective wisdom can lead to sifting effect, 「integrity and variability」 leads to efficiency, and 「negative feedback」, 「inhibition」 lead to system stability. This research is believed to provide some managerial guidelines for web 2.0 sites operation.

千年以來，人類不斷遭遇各種疫病的侵襲，流行速度更勝戰火蔓延，影響整體人類重大，然而隨著醫學知識的進步與衛生環境的改善，許多傳染病已經受到控制乃至根絕，但是生活周遭仍然面臨諸多威脅生命健康的潛藏危機，如果稍有疏失或不慎，傳染病不僅對於人體造成傷害，甚至恐將危害社會、經濟和政治層面，而近年的SARS、H1N1等流行病毒皆造成全球恐慌。 防疫工作重點在於及早掌握疫情趨勢以利制定相關因應政策，目前各國對於傳染病的掌握主要透過層層監測系統與歷史平均，藉以判斷該年特定傳染病流行與散佈程度。這些方法受到各種人為與環境因素影響，導致推估疫情成效有限之外，同時所得資料無法直接反應未來疫情，因此導致各國相關單位逐漸嘗試其他預測方法。 近年應用預測市場機制預測疫情模式引起公衛領域的重視，相關學術期刊與著名雜誌相繼介紹此一新興模式，同時肯定其在預測傳染病方面的成效與貢獻，而美國和台灣政府部門先後透過此項機制改善現有防疫體系的不足。那麼，預測市場用以預測疫情的成效是否確實如同其在眾多領域取得的成效一樣出眾？鑑於前述問題，本研究分別透過質化與量化的方式發掘公衛、醫學或流病學等其他領域對於「傳染病預測市場」是否能夠成為有效的預測機制或是成為常規的參考方法，結果證實使用的疾管局人員與參與的專業醫事人員認為「傳染病預測市場」確實可以應用於我國疫情預測的層面，但是兩者意見具有程度的差異。 / For centuries, the spread of various diseases damage countless human beings, which surpass wars in the world. Those diseases not only endanger people’s life, but also invade the other dimensions, including society, economic and politics. With the advancement of medical knowledge and the improvement of public health, many infectious diseases have been brought under control and even eradicated. But humans still face and experience threats from pandemic viruses such as SARS and H1N1 constantly. Epidemic prevention work focuses on understanding the variation of situation as soon as possible. Then governments can set up suitable decisions and policies based on epidemic situation. Though the monitoring system and the historical average are the mainstream to control the trends of infections for related departments, scientists believe that the two methods are subject to humans and environmental factors. In other words, it is difficult to draw effective information and direct response of the future trends from present methods. And it leads to national units gradually try other epidemic forecasting methods. In recent years, using prediction markets to predict flu causes the attention of public health. Thus academic journals and well-known magazines not only introduce this application but approve its effectiveness and contribution in predicting infectious diseases. The departments of US and Taiwan have tried to improve the deficiencies of the existing prevention system through prediction markets. Is this application really as successful as PM in many issues and fields? To response the question, this research intends to through qualitative and quantitative ways respectively to explore the evaluations on Epidemic Prediction Markets behind public health, medical, epidemiology, etc. The result confirms that CDC staff and health workers identify the feasibility of Epidemic Prediction Markets, but with the degree of variation.