適地性服務(Location-based services, LBS)為利用行動裝置及無線網路來獲取基於使用者所在地理位置的資訊服務，近幾年日益受到重視。以推播（push）方式提供之服務稱為位置感知服務(Location-aware services, LAS)，其最大特色為伺服器端可主動提供資訊給使用者。雖然這項優勢能讓資訊提供商主動尋找候選人用戶，以提高服務之價值，但其成功必須仰賴正確且有效掌握使用者需求及依情況篩選推播之資訊，否則使用者可能對於連續的垃圾訊息感到厭煩，並失去使用此服務的興致。本研究提出個人化位置感知系統(Personal Location-Aware Services, PLAS)之概念，探討行動用戶所面臨的各種情況，整合包含空間、時間、使用者興趣及當前活動等情境之約制條件及個人資料、行程表、事件等資料，發展為基礎於個人需求之情境感知資訊推薦服務。以校園資訊為例，PLAS系統之演算法可依學生之時空條件及情境狀態而推薦合適參加之活動資訊，並隨時根據使用者移動、時間推移及事件之更新而動態調整服務之內容。在持續精進所包含之事件種類及選取知識後，PLAS可進一步擴展為更為全面之個人行程規劃系統，依據規劃之行程主動通知使用者該前往下一行程地點之時間，用以提供行動用戶符合時空條件之個人化資訊，並提供行程規劃以增進使用者於空閒時間管理之效率。

Location-based service (LBS) is an information service accessed by mobile device and wireless internet based on user’s geographical location, it has been popular in recent years. Among a variety of LBS, push mechanism allows servers to automatically push information to the users, so-called location-aware services (LAS). Although LAS enables information providers to actively locate and provide information to candidate users for increasing the service value, it is success heavily relies on the accurate selection of information based on users’ personal needs and situation, to avoid annoying or even garbage information. In this research, a Personal Location-Aware System (PLAS) is proposed by analyzing the situation mobile users may encountered, considering the spatial, temporal factors, user’s preferences, and current activity and utilizing a user’s personal profile, schedule and event data as resources to develop a context-aware recommendation service based on personal requirements. Take campus information as an example, the developed algorithm in PLAS can adapt to the users’ continuously changed location and adjust the information pushed according to this user’s contexts and spatial-temporal condition. The recommended events are dynamically adjusted according to the user’s movement, remaining time, and the updating information on the event. In the continuous improvement of the types of events and the event selection knowledge, PLAS can further expand to personal travel planning system, and remind the time user must depart for the next destination, in order to provide mobile users with not only personalized information meets the spatio–temporal constraint, but the travel plan for user to follow in their leisure time.

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