近年來由於行動商務應用的蓬勃發展,對於使用行動裝置的使用者而言,其便利性增加了不少,而行動應用服務越來越多元化,其中代表性的行動服務即為適地性服務與行動化推薦。而現在行動應用更加入了社群化的服務,透過社群網路中人與人之間的推播分享,讓行動應用服務發展更往前邁進了一步。然而,有關行動推薦的部分,其推薦模式鮮少有情境資訊結合社群網路的概念作為推薦的依據,因此,本研究提出了適地性服務結合情境資訊與社群網路的推薦系統概念,並且運用協同過濾與社會網路分析方法來設計推薦雛型系統機制。而所設計的雛型系統會透過使用者的操作來分析推薦結果的準確性,最後提供簡短的問卷讓使用者發表一些意見,驗證系統的便利性與觀察使用者操作後的接受度與滿意度。最後的結果也驗證了LBS情境資訊加上社群網路的推薦結果準確性的確比一般的推薦結果來得高,也給未來在行動應用服務上有很好的參考價值。
In recent years, mobile commerce application development positive. It makes users who use mobile-device become very convenience. Mobile application also become diversification, Location-Based Service and Mobile Recommendation are on behalf of mobile application service. Now, mobile application mix in social network. Through push and share in social network, it let the development of mobile application will a step forward. However, mobile recommendation`s mode has not basis by the combination of context-aware location-based services and social network. Therefore, this study proposes the concept of combination of context-aware location-based services and social network recommendation systems. Use Social Network Analysis and Collaborative Filtering to designed recommendation systems. Then this study look for some users, they must operating this system and write web questionnaire in order to verification accuracy of recommend result and accepted and satisfaction by users. Final result proves accuracy of recommend result of the combination of context-aware location-based services and social network is better than general recommend result. It is a good reference value on mobile applications service.
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