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  • 學位論文

應用案例式推理與Web 2.0技術於商家推薦系統之研究

The Study on Application of Case Based Reasoning and Web 2.0 Technology in the Business Recommendation System

指導教授 : 王淑玲
共同指導教授 : 林春宏(Chuen-Horng Lin)

摘要


隨著網路技術的發展,Web 2.0的網路服務已成主流,民眾開始將生活瑣事記載於個人Blog以及在各社群網站分享自身的經驗,網路逐漸形成一種商品口碑傳播平台。民眾利用網路搜尋消費資訊,藉由他人的消費經驗分享,來決定消費的商家,但資訊量隨著時間愈來愈多,已造成資訊超載現象,民眾在面對眾多的選項上,花費過多的時間與精神在搜尋所需要的資訊。 因此,本研究設計一個商家推薦系統的服務平台,首先以台中市餐廳為例,當使用者需要選擇餐廳時,藉由使用者提供的條件資訊,利用案例式推理來篩選使用者當下條件選擇的結果,搭配內容式推薦演算法來輔助使用者查詢條件不足的情形,系統主動推薦餐廳目錄給使用者,提供個人化推薦的服務,並藉由使用者的回饋逐漸擴增案例庫,和改善系統的推薦準確率。本研究將建置一以Web 2.0為基礎之平台以應用於商務應用。 本研究以實驗測試的方式來評估系統可用性,於使用者測試系統後進行問卷調查,以了解使用者是否滿意系統推薦結果,經由統計分析得知本系統具有可用性。本研究成果可供其他店家推薦系統之參考。

並列摘要


With Internet technology development, Web 2.0 for web service has become mainstream, people began to record their daily life in their Blog and various community sites to share their life experiences. Therefore, Web service becomes a communication platform gradually. However, people can use the Web service system to search for information of consumption and experience sharing by the consumption of others to determine how to consume. But, the amount of information over time more and more, has resulted in information overload. Therefore, people always acquire many options, spend too much time and efforts in their searching information task. This study designs an e-commerce recommendation system with web service function, a case study of restaurants in Taichung city. When users need to acquire consuming information of restaurants, they can apply this recommendation system for acquiring the information they need. The system automatically recommend restaurant information list to users, offers personalized recommendation service, and expansion of case base gradually by the user's feedback, and improve the accuracy of recommendation system. However, this study concludes with ideas for Web 2.0 applications of recommendation system to e-commerce. In the study, the way we use experimental testing to assess system availability, in a user survey conducted after the test system to see whether the user is satisfied with the system recommended a result, by statistical analysis that the system has available. The research results available to other business recommendation systems of reference.

參考文獻


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