個人化複合式電子服務推薦之實作

Abstract

隨著網路資源的蓬勃，電子商務市場產生劇烈的變動，強烈影響使用者的服務需求型態。然而企業所提供的單一電子服務已經無法滿足使用者需求，因此，企業開始與其他的電子服務提供者進行協同商務的整合，來發展複合式電子服務流程，以便提升本身在市場的競爭能力。複合式電子服務是多個基單一的電子服務所組成，其所帶來的附加價值遠高於單一的電子服務，再者，為了能夠在電子商務的環境中提供一對一行銷的服務，因此個人化推薦系統的建置也日趨重要。但僅管目前有許多平台紛紛提出複合式電子服務，但仍未見到針對複合式電子服務來進行個人化推薦之系統。 有鑑於此，本研究將運用合作式過濾方法以及資料探勘技術建置一個以複合式電子服務流程為主的個人化推薦系統，其目的在於將個人化推薦系統整合於複合式電子服務平台上，使客戶能更有效的選擇複合式電子服務來滿足其服務需求。

With the explosive growth of information resources on the Internet, the electronic marketplace has changed dramatically, which strongly influences the customers’ behaviour of demands. Individual e-services cannot fulfill customer’s demands anymore. Therefore, recommender system are the solution that allow enterprises to develop one-to-one marketing strategies and provide adequate support to fulfill customers need to boost the success of online e-business. Enterprises need to provide various e-services and conduct composite e-services on the collaborative commerce environments, which aim to improve the market competitive advantages. There are two objectives in this research. Firstly, we propose a useful personalized recommender system that combines collaborative filtering method and data mining techniques for generating composite e-services recommendations. Secondly, we provide an integrated knowledge map navigator with personalized recommendations in our proposed composite e-services platform. We expect not only to reduce the complexity and cost for the e-service providers online, but also to fulfill user’s needs online.