本研究於個人數位註釋應用程式iPARIS上，建立影像標籤註釋之功能，稱為iPARIS-PLUS。它提供不同於以往文字註釋的新方法，讓使用者可以有另一種選擇，也同時解決在面臨多國語系時的註釋問題，並有效的降低記錄所花費之時間。iPARIS-Plus能讓使用者保有在行動裝置上紀實之便利性的同時，也能兼顧記錄的完整性，讓人們不再將記錄視為一種麻煩。除此之外，我們透過群眾外包的力量將用於註釋的影像標籤轉換為文字後儲存於資料庫中，解決原先因多國語系註釋問題讓使用者無法輸入文字，導致資料庫缺少該筆資料而造成資料空缺。在評估方面，受測者認為影像標籤註釋之方法可以有效的解決多國語系註釋之問題，以及有效節省在行動裝置上打字之時間，更加強了記錄的便利性與完整性，同時也帶來不同以往的新鮮感。而我們藉由群眾外包得到良好的解析率，並且從歷程記錄中發現群眾外包於運作上，越多專業之群眾並不一定帶來越好的成果，只仰賴少部分專業之群眾提供貢獻，反而能減少問題產生，進而得到較好之結果。 / In this study, we created the function of image tags annotating in the application, iPARIS-Plus. It provided a new method of annotation which is different from the text annotations, therefore, users could have another choice. This function could solve the problem of multilingual annotation and reduce the time effectively when users take for the record. iPARIS-Plus allows users to retain the convenience of recording on their mobile device, at the same time, it also considers the integrity of the records, so let people will no longer feel recording is a trouble. In addition, we converted the image tags that used to annotate into text through the crowdsourcing system to solve the problem which users couldn’t enter text because of the multilingual annotation, it resulted in a lack of databases. In the evaluation, users argued that the image tags annotation method could solve the problem of multilingual annotation effectively, as well as saving the time they typing on their moblie devices, even more it can enhance the integrity and convenience of records. We got a good resolution rate of converting the image tags into text by crowdsourcing system and found that more professional crowds do not bring better results. On the contrary, we could rely on a few of professional crowds to reduce the problems, then got a better results.

中國有句諺語:「民以食為天」，食物乃人類生活所不可缺的要素之一，而人們對於食物則有各自的偏好，而要從琳瑯滿目的食物中依照個人喜好來推薦則成為一門重要的課題。 隨著科技的進步，智慧型手機的出現為人類帶來了許多便利，也逐漸改變了人們的生活方式，群眾可以透過智慧型手機來記錄生活的點滴，記錄的方式正走向數位化，而如何利用這些累積下來的數位資料來做分析與推薦也成為熱門的研究目標。 本論文從味覺方面著手，將LifeLog的飲食記錄與味覺做結合，並透過大眾分類與群眾外包的方式，將味覺資料由智慧型手機使用者處獲得，並建構成包含餐廳、餐點名稱以及其對應味覺之資料庫。 本論文實作了一個程式Foodtaste，包含了記錄餐點味覺資料，查詢個人記錄，以及實作數種推薦的功能。本論文並提出了數個計算方法，透過LifeLog累積下來的味覺資料進行計算，來獲得每位使用者的個人口味偏好和味覺比例，並將這些資料與餐點的味覺比例計算來對餐廳進行個人化的餐點推薦。 / Foods and eating are the basic element of human's life, and people have their own favorite in choosing foods. Thus it is an important issue to make some recommendation for people in front of a dazzling array of foods. With the advances in technology, smartphones bring convenience to people and change their life style. One can use smartphones to record various things in his life. The ways of memories become digitalized, and how to use these digital data to analyze and give opinions becomes popular. Base on one’s taste, present study combined dietary records and food taste in Lifelog, using Folksonomy and Crowdsourcing to acquire data of specific food taste from smartphone users, and linked these data to restaurant’s name and the name of the meal in our database. We designed a smartphone application which called "Foodtaste". It provided users to record what they ate and how did it taste, looking up personal records, and several recommending methods. Our study also provides several methods in calculating cumulative data in Lifelog and acquiring the preference of one’s taste and ratio in variable foods from every user. Then we calculated these data to carry out personalized food recommendation.