行動裝置在現在這個世代相當普遍，而我們需要一個方法來探索App在背後的行為。 本研究提出了一個非監督式的分群方式，目的是在於探討我們是否能使用App中的原始碼當作以行為分群的依據。 在此研究中，我們應用了迭代分群的方式對Apps做分析，並且觀察分群的結果是否恰當。 而在實驗中，我們由App Store下載了數百個App並加以分析，我們發現我們所提出的方式表現相當良好並且能給出正確的分群結果。 / Smart devices are everywhere nowadays. Mobile application (app) development has become one of the main streams in software industry with more than millions of apps that have been developed and published to billions of users. It is essential to have a systematic way to analyze apps, preferably on their executable that are the only public available sources of apps in most cases. In this work, we propose to apply unsupervised clustering to mobile applications on their system call distributions. This is done by first adopting a static binary analysis that reverses engineering on executable of apps to find method call/sequence counts that are embedded in apps. Apps are then clustered iteratively based on this information to reveal implicit relationships among apps based on function call similarity. The GHSOM (Growing Hierarchical Self-Organizing Map), an unsupervised learning tool, is integrated to cluster apps based on the information resolved from their executable directly. We use types of methods and sequences as features. To run the clustering algorithm on apps, however, we immediately confront a problem that we have a large amount of attributes and data that leads to a long/infeasible analysis time with GHSOMs. The new iterative approach is proposed to conquer this problem along with dimension reduction with principle component analysis, cutting attributes with limited information loss. In the preliminary result on analyzing hundreds of apps that are directly downloaded from Apple app store, we can find that the proposed clustering works well and reveals some interesting information. Apps that are developed by the same company are clustered in the same group. Apps that have similar behaviors, e.g., having the same functions on games, painting, socializing, are clustered together.

WHO的一項全球性調查顯示，全世界真正健康的人佔5%，經診斷有疾病的人佔20%，處於亞健康的人佔75%，伴隨著慢性病所造成的死亡率也跟著增加，生活的品質已成為大眾們所關注的焦點，因此國人已有如何自主管理健康取代經常性的藥物治療，以增進健康的生活品質之意識。隨著國人對於自我健康管理的認知，如何滿足有效的管理健康需求的增加，已是大家探討的熱門議題。針對此一議題，本研究以健康促進處方為核心，整合個人化的生理健康數據如血壓、血糖、膽固醇、生活習慣、工作型態等進行健康風險評估，進而推薦適合的個人化健康促進處方，搭配運動器材、行動應用程式(Mobile Application)、雲端運算平台、體適能中心之運動生理監控，未來可適用於企業自行發展出的一套「雲端個人化健康管理平台」，有效支持個人運動安全並培養定期的運動習慣，達到健康促進的目標。

隨著網際網路與資通訊科技的高度發展，企業打造多元的APP改變經營模式，同時政府機關為了提升政府運作效能與國家競爭力，亦設置了多元的行動化服務。新服務模式跨越了傳統時間與空間上的限制，對於傳統的代議政治體系中提供了更符合公民直接參與的機會。近年來，電子化政府的發展更被廣泛地賦予民主意涵，電子民主成為公民參與與政府治理之新溝通模式。 本研究透過電子公民參與相關研究文獻之彙整，盤點及歸類現行中央與地方政府所提供的APP服務與電子公民參與之間的關係。再者，根據分類的結果，針對擁有電子化決策參與精神的APP服務建構評估指標，本研究挑選臺北市長信箱以及阿倫Online作為參照個案，同時彙整網站服務品質指標、國內外電子化政府評估研究、政府服務滿意度評估研究、電子商務滿意度研究、首長信箱滿意度評估架構，以及結合網路資源等六類文獻，提出政府APP評估構面與操作化指標，並透過兩回合的結構式問卷訪談修改指標架構及內容。 本研究經結構式問卷訪談進行資料收集後，將政府APP評估構面與操作化指標區分為兩大主構面：系統品質以及公民參與與服務品質。前者，進一步細分出（1）視覺設計、（2）易用性、（3）安全及隱私等三大次構面，其中，視覺設計共有九項指標，如：APP名稱清楚明確，並能凸顯其具備陳情抱怨的特質、APP簡單整潔；易用性共有十九項指標，如：APP在點選後3秒內，能執行完畢、APP的功能簡單、便利；安全及隱私共有四項指標，如：APP所需的資訊與權限可以被接受、APP所需的個人資料項目可以被接受。 後者，細分出（1）互動及回覆內容品質、（2）有用性、（3）反應性、（4）效能感等四大次構面。其中，互動及回覆內容品質共有四項指標，如：主管單位回覆的資訊是充足的、主管單位的回覆是正確的；有用性共有三項指標，如：相較於臨櫃服務、1999與網頁版首長信箱，APP能更快速解決我陳情抱怨的問題、無須再透過其他系統或平台申辦帳號密碼，便可完成陳情抱怨程序；反應性共有六項指標，如：透過APP，政府機關能快速地接收到我的陳情、主管單位的回覆語氣與方式親切有禮；效能感共有三項指標，如：陳情通知或回覆的內容，讓我覺得主管單位了解我的困難及問題癥結、我認為主管單位的通知或回覆內容係針對我的需求與問題提供服務。總計有二大主構面、七大次構面，以及四十七項指標。同時依據每項指標對於APP意義程度上的差異，將指標區分為基本指標（must have）以及進階指標（good to have）兩種層次。 期望本研究建構的指標架構，除了可做為未來政府機關開發電子化決策參與APP的參考依據外，同時有助於主管機關改善及永續現行APP之經營與發展，並且強化APP的安全機制，邁向資訊開放及運用。後續研究可深入探討無障礙與安全性指標內容設計，待部分指標進一步操作化後，可運用德菲法讓指標項目具一致性，並採用AHP搭配深度訪談擬定指標權重，最終以大量發放問卷了解指標合適度以及了解APP的發展現況。 / The expansion of the Internet and the fast development of information communication technologies (ICTs) have changed service deliveries of enterprises and government organizations. Many enterprises change the service model with creating a variety of APPs. Government organizations, meanwhile, provide multiple mobile services in order to maximize the competitive advantage of nations. A novel service model breaks restrictions on time and space, providing the opportunity of direct democracy for the public. Lately, the development of electronic government is entitled to extensive democracy, and electronic government becomes a new communication model. In order to realize the meaning of e-democracy and the development of governments’ online services, this research reviews the literature of electronic democracy. The author use three dimensions, including ‘electronic information’, ‘electronic service and consultation’, and ‘electronic decision making and participation’, to categorize APPs created by central and local governments. Base on the previous findings, this research selects electronic decision making and participation of APPs to construct indicators. The author reviews six types of literatures, including web service quality indicators, electronic government assessment, governmental service quality research, electronic commerce satisfaction, mayor's email-box satisfaction, and Internet resources to establish indicators of governments’ APPs. The framework and contents of indicators are revised by implementing two rounds in-depth interviews with the questionnaire. According to empirical data, this research separate indicators into two dimensions, including System Quality and Citizen Participation & Service Quality. The System Quality has three sub-dimensions, including Visual Design, Ease of Use, and Security & Privacy. Visual Design has nine indicators, such as the accuracy of APPs’ title, the simplicity of APP, etc. Ease of Use has nineteen indicators, such as the response time less than three seconds, the simplicity of APPs’ functions, etc. Security & Privacy has four indicators, such as the authority of being acceptable, proper personal informations, etc. The Citizen Participation & Service Quality has four sub-dimensions, including the Contents’ Quality of Interactions, Usability, Responsiveness, and Efficacy. The Contents’ Quality of Interactions has four indicators, such as the sufficiency of governments’ reply, the accuracy of governments’ reply, etc. Usability has three indicators, such as relative to APPs’ deal of speed than counters, 1999, and the mayor's email-boxes, applying for accounts directly in APP, etc. Responsiveness has six indicators, such as immediately response, courteous reply, etc. Efficacy has three indicators, such as understanding of the petition, customize services, etc. To sum up, indicators of government APPs have two dimensiosns, seven sub-dimensiosns and forty eight indicators. Base on those indicators, and this research further categorizes them into ‘must have’ and ‘good to have’. This framework of indicators is expected not only becoming the reference for government organizations creating APPs in the future but also improving service quality of APPs nowadays. Moreover, it is important that having to strengthen APP’s security and privacy, then governments could open data from citizen complaints and use them to create new value. Future research could explore the disability and security aspects of indicators. Moreover, future research could consider operationalize a part of indicators, and then adopt Delphi and AHP to measure robustly the consistency and weighting of indicators. Finally, the author expects the follow-up studies could conduct questionnaires to realize the fitness for indicators and condition of APP’s development.

隨著新生活娛樂型態興起，以及可攜式行動裝置愈來愈普及，行動廣告的重要性也與日俱增，品牌行動應用程式與消費者的高互動特性，已引起行銷人員相當大的興趣，承載品牌識別圖案與訊息的品牌行動應用程式，無疑是最新崛起的行銷戰場。然而本研究認為，品牌行動應用程式不單純只是品牌的廣告，實際上也是品牌延伸後的新產品，因為它提供使用者不同於原品牌的新功能與服務，且擁有一套獨特的設計理念，因此，本研究在探討行動應用程式互動的效果時，還加入了“品牌延伸”的概念。 　　本研究選擇五個品牌行動應用程式為研究主體，依照受測對象為使用者與非使用者，調整問卷內容與次序，共設計十份問卷。資料分析結果證實，消費者與品牌行動應用程式的互動而產生的媒體經驗，確實能提升其母品牌的態度；由品牌延伸的角度，研究結果亦證實，品牌行動應用程式與母品牌的認知契合度越高，消費者對品牌行動應用程式的態度就越好，而且品牌延伸存在正向的外溢效果，意即品牌行動應用程式的好感會正向回饋至母品牌的態度。另外，本研究發現體驗型的品牌App較能觸發多元、獨特、且專屬於該品牌的聯想。 　　本研究的結果不僅可以提供廠商在使用品牌行動應用程式作為行銷工具時的參考，更能在廠商實際建置品牌行動應用程式時，建議提供何種互動經驗給目標消費者較為適當、設計的概念是否要與母品牌概念一致、或者依據行銷目標的不同，推出不同類型的品牌App。

摘要 　　觀光旅遊是現今十分興盛的休閒活動，根據 2010 至 2012 年交通部觀光局統計資料顯示，國人國內旅遊以非旅行社承辦平均高達約 88%，因此如何有效規劃行程內容及安排各景點間的交通路線，就成為旅遊前的重要準備工作。 　　檢視目前旅遊規劃的數位服務平台並無法真正解決旅遊需求。故本研究設計與建置一套旅遊支援平台，首先藉由訪談，了解使用者需求，歸納出平台設計重點，分析系統的使用流程，再設計功能模組化與操作介面，最後建置平台並進行原型評估。本平台以雲端資料庫為基礎，無縫結合網站與行動應用兩端的資訊流。使用者在行前利用網站規劃行程內容，完成後上傳至雲端資料庫，網站端內容會自動同步於行動應用端，並以適合行動應用的界面呈現。使用者之行程安排因此更便利與彈性，在行動中亦能利隨時以手機查看行程，並依當地情況修改行程、即時安排交通路徑，使得旅遊行程計畫可以依實際的變化機動調適。而更新後的行程亦同步儲存於雲端。 　　本研究未來方向可以往更多的服務串流發展，如景點的多媒體內容、社群結合、智慧邏輯排程或外部資訊連結等等。隨著未來資訊技術的提升，將為系統平台帶來更多可能性、讓整體服務擁有更佳的整合性，提供使用者更好的體驗。 / Nowadays, touring is a popular leisure activity. According to statistics from the Taiwan Tourism Bureau, people arranged their own domestic travels as high as 88%. Because backpacking can be economical and more flexible, many young people tend to travel by themselves. Therefore travel planning has become the most important preparation work. How to plan an effective schedule and how to arrange the routes between attractive points are the tasks that backpackers often need to face. However there are few information services for the needs currently. The thesis designed and implemented a travelling support platform. First, the research identified design key elements by interviewing users and analyzing travelling behaviors. Second, the research mapped the touring process into functional models. Finally, we built and tested the platform prototype. This platform is Cloud-based and seamlessly integrates both website and mobile application to achieve the information service. Users use the website to schedule their trips and upload the schedules to the cloud database. Then the user can access the same schedule made at website on the mobile APP synchronously. They can check their schedule while they are traveling on the mobile phones. In addition, they can edit the schedule and rearrange new traffic routes real-time to adjust to the local circumstances. The further developments of the platform will include more integrated services, such as multimedia contents, social network, and intelligent logic scheduling. With the evolution of the technology in the future, the platform will provide better user experience.

行動應用程式是當今最受歡迎和最主要的軟體應用程式，因此應用程式的實際行為以及相關的安全和隱私問題變得越來越重要。另一方面，隨著時間的推移，AppStore上有越來越多的應用程式已經停止更新或停止服務，但沒有從AppStore中刪除。然而，用戶對於缺少維護問題一無所知，仍然下載並使用它。在本研究中，我們將解決在應用程式中檢查特定屬性方法序列的問題。通過使用IDApro生成Function call dependency graph和Subroutine control flow graph，我們使用語法分析方式來進行跨子程式的序列檢查方案。我們將通過預先定義屬性的方法序列作為模型來檢查應用程式行為。這個分析方法可以說明在App Store中可用的應用程式中是否存在屬性方法序列。有助於我們在應用程式中檢查一些惡意行為屬性方法序列或特定行為方法序列（例如使用不推薦的api方法）。 我們的網絡爬蟲從官方文件中摘取了的所有可用的iOS SDK方法，並從中提取做為我們的模型序列。我們將檢查應用程式是否包含所準備的模型序列。如果應用程式中存在該序列，我們將在應用程式中記錄子程式中包含的方法序列調用。然後將結果數據匯總到我們的數據庫中，並將結果視覺化、數據化，並建立系統的的API服務。最後，我們構建了一個使用上述檢查功能所識做的的分析系統，並以Web服務形式顯示結果。 / Mobile application is the most popular and dominant software applications nowadays, so the actual behaviors of the application and the related security and privacy issues become more and more important. On the other hand, as time goes by, there are more and more applications on the AppStore stop to update or being abandoned but not removed from AppStore. However, the users know nothing about the lack of maintenance problems and still download and use it. In this research, we will resolve the issue for checking specific property method sequence within an application. By using IDApro to generate function call graph and the subroutine control flow graphs, we use syntax checking strategy to perform a across subroutines sequential checking solution. We will check the application behavior by predefining a property method sequence as pattern and then check with applications’. The analysis method can illustrate whether a property method sequence exists in the application which is available on App Store. This may help us to check some malicious behavior property method sequence or specific behavior method sequence (ex. using deprecated api methods) in the applications. We have prepared some property method sequence as our system input pattern extracted from all the available iOS SDK methods fetching by our web crawler. We will check whether an application contains the prepared method sequence or not. If the sequence exists in the application, we would record the method sequence call included in the subroutine within the application. Then the results data will be aggregated in our database, and export as api service for visualizing and statistic uses. Finally, we construct a call sequence analysis system for the above checking functions and show the result in a web service form

當今已有數以百萬計的行動應用程序在 Apple 的 App Store 中發布，並在iOS設備下載量超過150億次。為了保護iOS用戶免於惡意應用程式的傷害，Apple 對於上架之App 有相對嚴格的審查政策。通過審查的App才能在App Store中發布。在本文中，我們提出基於 iOS可執行檔的靜態字串分析技術用於檢驗App可能動態載入之類別 。為了檢查動態載入之類別是否符合Apple之規範，必須要能確定動態加載函數之可能字串參數值 。我們方法的第一步是使用現有工具擷取 iOS可執行檔的組合語言。然後自組合語言中建立整個程式的控制流程圖（CFGs） 。接著，在控制流程圖上識別動態加載類別的函數，並且對於該函數的每個參數，我們構造一個字串相依圖，用以顯示流向字串參數值的所有構成成分以及構成方式 。最後，我們對這些可能流向參數的字串進行字串分析，以確定這些參數值所有的可能值集合。透過把這些可能值與特徵值（從Apple 審查政策建構而來，例如私有/敏感性API），我們能夠檢測到App 潛在違背Apple政策之情形。我們分析了1300多種目前上架於App Store的App，並檢查他們是否違反蘋果關於使用私有API的政策以及 廣告識別碼（IDFA）政策。我們的工具提取了超過37000 這些App的字符相依圖，分析結果顯示208個App透過字串操作構組合出對應的API名稱並且有潛在的IDFA違規濫用之可能。我們的分析還發現了372個可以使用字串構建私有類名稱的應用程序和236個可以使用路徑字符串加載私有框架的App，這些App可能違反Apple 禁止使用私有API使用政策。 / Millions of mobile apps have been published in Apple's AppStore with more than 15 billion downloads by iOS devices. In order to protect iOS users from malicious apps, Apple has strict policies which are used to eliminate apps before they can be published in the AppStore. In this paper we present a string analysis technique for iOS executables for statically checking policies that are related to dynamically loaded classes. In order to check that an app conforms to such a policy, it is necessary to determine the possible string values for the class name parameters of the functions that dynamically load classes. The first step of our approach is to construct the assembly for iOS executables using existing tools. We then extract flow information from the assembly code and construct control flow graphs (CFGs) of functions. We identify functions that dynamically load classes, and for each parameter that corresponds to a dynamically loaded class, we construct a dependency graph that shows the set of values that flow to that parameter. Finally, we conduct string analysis on these dependency graphs to determine all potential string values that these parameters can take, which identifies the set of dynamically loaded classes. Taking the intersection of these values with patterns that characterize Apple's app policies (such as private/sensitive APIs), we are able to detect potential policy violations. We analyzed more than 1300 popular apps from Apple's AppStore and checked them against Apple's policy about the use of private APIs and the identifier for Advertising (IDFA). Our tool extracted more than 37000 string dependency graphs from these applications and our analysis reported 208 apps that compose the corresponding API with strings and have potential IDFA violations. Our analysis also found 372 apps that could have compose the private class name with string and 236 apps that could have load the private framework with path string; and could violate the private API usage policy.

隨著智慧型手機普及，大量行動應用程式(Apps)近年如雨後春筍般的出現，然而在大量且功能間相似的App中，如何脫穎而出實為值得探討之議題。 本研究依據先進者優勢作為理論基礎，並延伸探討產品特性及行銷策略對先進者優勢維持之影響，透過檔案分析法針對目前市面上數個成功的App進行個案研究，並同時對功能相仿的App進行交叉個案分析，期望歸納出能領導各種類App成功的方法。 本研究蒐集自期刊論文、相關書籍、報章雜誌及網路文獻之資料，經個案分析之研究結果如下： 1. 市場的先佔及高轉換成本為App先進者主要優勢來源；而較低的成本、市場不穩定性及先進者可能失誤，則為App後進者主要優勢。 2. 較佳的產品功能與產品創新能力，或較能提供更多附加價值之App，對App先進者優勢的維持有正向之影響。 3. 不同種類的App在先進者優勢之維持上略有差異，簡要歸納如下 (1) 遊戲類：受先進者優勢、產品優勢及行銷策略影響甚鉅，快速先占市場，並擁有良好產品功能及完整行銷策略較易帶來成功。 (2) 工具類：透過較佳的產品功能、產品品質與產品創新來維持先進者優勢，才能保持長期競爭力。 (3) 娛樂類：先進者優勢與產品優勢同等重要，快速先占市場將有助於發展與競爭力維持。 (4) 社交類：深受網路外部性之影響，故快速先佔市場並持續滿足使用者需求，才能避免被後進者淘汰。 / As more people use smart phones, the number of mobile applications (Apps) is increasing rapidly. However, with so many similar Apps, how Apps can stand out from competing products is an important issue. This study adopts theories related to First-Mover Advantages, Product Advantages and Marketing strategies to develop a general framework for analyzing factors that affect the success of first movers. We chose several well-known apps and used document analysis to analyze the secondary data collected from the Internet, newspapers, magazines, books, etc. Our major findings are as following: 1. Market preemption and high user switching costs are the main source of advantages for first-movers. Lower development costs, risks and the chance to avoid failure are the main source of advantages for the follower to succeed. 2. Better product functions and innovative features have positive effects on keeping First-Mover Advantages. Meeting customer needs and providing more added values also help maintain the advantage. 3. Different factors exist for different types of apps. Product advantages and marketing strategies are keys for Games Apps; app functionality, product quality and innovative features are important for productivity tools; first-mover and product advantages are important for entertainment apps; while network externality is the most critical one for social networking apps.

新科技的變遷總是為傳播產業帶來新的變革，智慧型手機掀起全球通訊產業的熱潮，造就了行動應用程式新經濟，進而帶動行動應用程式廣告的發展。有鑑於過去研究缺乏以解構計畫行為理論的角度，來探討近年才趨於熱門的行動意用程式，更缺少應用在某特定行動應用程式類型之行為意圖。本研究將以Taylor & Todd（1995)解構計畫行為理論，聚焦於社群媒體廣告研究，並以在社交類型App的龍頭Facebook為研究對象，試圖釐清Facebook行動用程式廣告之行為意圖。 本研究採線上問卷調查法，以非隨機抽樣中的立意抽樣（purposive sample）為蒐集資料的方法，以結構方程模式（Structural Equation Modeling, SEM）為資料的統計分析方法。問卷發放於Facebook以及台大批踢踢實業坊（ptt.cc）符合研究主題的討論區進行資料蒐集，問卷連結日期自二0一五年一月一日至一月十六日，為期十六天，有效問卷共計五百一十一份。研究結果發現：(1) Facebook App的知覺有用性、相容性和知覺娛樂性，與廣告整體態度無顯著關係。(2)廣告內容的「娛樂性」與「個人化」有助於廣告態度的影響；「資訊性」與廣告態度無顯著影響，「煩躁性」與廣告態度則呈現負相關。(3)人際影響、自我效能和廣告態度，與行為意圖皆呈現正相關。 本研究證實，對於使用者來說，相較於電腦版使用經驗與習慣，Facebook App仍有改善空間。此外，Facebook App的廣告內容是否具有完整的廣告資訊已不再首要因素，重要的是，該廣告是否具有娛樂性質和符合個人需求，在不讓使用者感到困擾的情況前提之下，吸引使用者的注意、滿足使用者的需求。同時，本研究證實人際影響、自我效能和廣告態度對行為意圖的正向影響性。 / Technology advancement has brought many new changes to the mass media communication industry. Smartphones revolutionized the communication industry by creating the mobile app economy, which lead to the development of mobile app advertisement. Past studies have not taken the decomposed theory of planned behavior into consideration when examining mobile applications that have gained popularity in recent years, let along behavioral intentions, which apply to certain types of mobile applications. Keeping that in mind, this study will focus on advertising within the current social networking industry leader, Facebook, using the above theory by Taylor & Todd (1995), in order to determine the behavioral intention behind Facebook’s mobile application advertisement. Data used in this study was collected through online questionnaires using the purposive sampling method, and analyzed using structural equation modeling. The questionnaires were distributed on Facebook and sections within ptt.cc that fit the research purpose of this study. Online questionnaire was open from January 1st to January 16th of 2015, spanning a total of 16 days. A total of 511 valid questionnaires were collected. The results of this studies revealed that (1) the perceived usefulness, compatibility, and enjoyment of Facebook app are not related to attitude towards advertisement within the app. (2) Entertainment value and personalization of the content of the advertisement positively affects attitude toward advertisement. Informativeness has no significant impact, while irritation negatively affects attitude towards advertisement. (3) Social influence, self-efficacy and attitude towards advertisement all show positive relation with behavioral intention. This research has proven that when examining user experience, Facebook app still has room for improvement in comparison with the computer version of Facebook. Also, whether Facebook app advertisement contains complete information is no longer the most important factor. Entertainment value and personalization, whether the advertisement can satisfy the above needs without troubling users, are now the most important points of consideration. Finally, this study has proven the positive effect social influence, self-efficacy and attitude towards advertisement have on behavioral intention.

全球每日產出的資料量持續成長，龐大的資料量、雜亂的資料檔案格式造成資料處理的困難；此外，全球智慧型手機的出貨量持續上升，未來將會至少人手一台行動裝置，同時行動網路的效能提升將可負荷更多的資料流量，行動工作者的數量也因此逐年增加。對商業智慧系統而言，透過企業資料的分析可以發現資訊之間的關連與隱藏其中的事實，讓使用者掌握更多的知識用於決策，分析的資料來源越豐富，其可提供做為決策用的訊息就更為準確。 　　過往商業智慧透過關聯式資料庫處理資料來源及電子郵件的通知使用者，但是龐大的巨量資料遠超過前者所能有效處理的數量，進而造成對資料擷取、保存、使用、分享以及分析時的處理難度；後者對於外出的使用者來說，電子郵件僅只是收到通知而已，使用者依然得需要電腦才能觀看分析報表。 　　故本研究使用雲端運算分散儲存及運算的技術及行動裝置隨手可得的特性解決前述的兩個問題，先透過雲端資料庫加速處理巨量資料的存取並製作成資料倉儲供商業智慧使用，接著透過行動應用程式即時接收推播訊息並呈現分析報表於行動裝置上。 　　在實作中，利用非結構化資料庫進行資料的存取，比起過往的關聯式資料庫確實可以有效提升巨量資料處理的速度；透過行動裝置的報表呈現，在平板電腦有較佳的成效，在手機上則是因為螢幕大小的關係，畫面呈現效果較差，這方面則有待改善。 　　本研究透過非結構化資料庫及行動應用程式設計新的行動商業智慧解決方案，實作雛型系統，並且透過異常申報健保費用醫院為案例，進行系統整體的測試，證明其架構及運作模式之可行性。經過驗證，本系統將能提供使用者使用巨量資料做為分析數據，並且透過行動應用程式立即取得分析報表。 / The volume of daily output data continues to grow world- widely. The huge amount of data and the disorder of data format cause the difficulty of data processing. Additionally, the number of smartphone sales is continuously growing, so everyone will own at least one smartphone in the future. In the meantime, the effectiveness of mobile internet and wireless is largely improved, so it can be loaded with more data flow. Because of this phenomenon, the number of mobile workers will be increasing per year. For business intelligence systems, through the analysis of enterprise's data we can find the relevance and facts hidden in information, allowing users to acquire more knowledge for decision-making. The more data sources we analyze, the more accurate information can be used to make decision. 　　In the past, business intelligence processes data sources through relational database and uses e-mail to notify users. However, the huge amount of data exceeds the number that can be effectively processed by relational database. On account of this, it becomes difficult regarding data acquisition, storage, application, sharing, and analysis. As far as the users are concerned, they only receive notifications by emails, so they still need a computer to view the analysis report. 　　In this study, I use cloud computing technology and mobile devices to solve the two aforementioned issues. First, we speed up the process of big data in data acquisition through Hadoop Hbase, and made it into data warehouse for Business Intelligence use. Secondly, we use mobile applications to receive push messages instantly and present analysis reports. 　　In the practical work, I use NoSQL database to acquire and store data. Compared with relational database, we can indeed effectively enhance the speed of big data processing. In reports’ presentation on mobile devices, the Tablet has better user experience then the phone. The phone is displayed comparatively poorly because of its small screen. This part needs to be improved. 　　In this research, I conceive a new solution of mobile business intelligence through NoSQL database and mobile applications, and implement this method into a prototype system. Moreover, through an example of the analysis of hospitals which have anomalous health-insurance reporting expenses we can test the whole system. It proves that this system’s structure and the mode of operation are feasible. The system will be able to provide big data as the source of analysis and present reports immediately through mobile devices to users.