請用此 Handle URI 來引用此文件:
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/28540
標題: | 透過階層型貝氏網路達成智慧型家庭之多人偏好學習系統 Multi-user Preference Model via Layered Bayesian Networksin a Smart Home Environment |
作者: | Zhi-Hao Lin 林志豪 |
指導教授: | 傅立成 |
關鍵字: | 智慧家庭,家庭自動化,偏好學習,服務提供,多人環境, Smart Home,Home Automation,Preference modeling,Service rovision,Multi-user Environment, |
出版年 : | 2007 |
學位: | 碩士 |
摘要: | 在智慧型家庭環境中如何根據居住者的偏好提供適當的服務是一個重要課題。本文的目標是建立一個系統能學習多個居住者的偏好並能適切的表示使用者之間的關係以及服務和感測器觀測資料的關係。因此可以基於學習後的偏好模型推論多個居住者所偏好的服務。所以我們提出一個三層偏好學習模型。在第一層中,從感測器所得到的原始數據中清除雜訊再被轉換成具有意義的高階資訊。
在第二層我們利用動態貝式網路模型考慮觀察資訊的相對時間關係來推論 各個居住者分別所想要的服務。 在最高層中,我們把第二層推論的結果、環境資訊和多個居住者間的關係來 推論目前在環境中居住者所需要的服務,並透過服務建議機制推薦服務給居住 者。 在實驗中,我們證明了我們的模型可以在智慧型家庭環境中推薦可靠和準確 的服務給居民。 An important issue to be addressed in a smart home environment is how to provide appropriate services according to the preference of inhabitants. In this paper, we aim at developing a system to learn a multiple users’ preference model that represents relationships among users as well as dependency between services and sensor observations. Thus, the service can be inferred based on the learnt model. To achieve this, we propose a three-layer model in our work. At the first layer, raw data from sensors are interpreted as context information after noise removal. The second layer is dynamic Bayesian networks which model the observation sequences including inhabitants’ location and electrical appliance information. At the highest layer, we integrate the results of the second layer, environment information and the relations between inhabitants to recommend the service to inhabitants. Therefore, the system can infer appropriate services to inhabitants at right time and right place and let them feel comfortable. In experiments, we show that our model can reliably recommend and precise services to inhabitants in a smart home environment. |
URI: | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/28540 |
全文授權: | 有償授權 |
顯示於系所單位: | 資訊工程學系 |
文件中的檔案:
檔案 | 大小 | 格式 | |
---|---|---|---|
ntu-96-1.pdf 目前未授權公開取用 | 2.87 MB | Adobe PDF |
系統中的文件,除了特別指名其著作權條款之外,均受到著作權保護,並且保留所有的權利。