因應網站製作需求,本研究依據Velásquez et al.(2011)擷取關鍵物件方式與Roth et al.(2010)三網站類型(線上購物,線上資訊與公司)的相關研究,作為網站首頁自適性配置研究的主要方法。根據這些方法,本研究實作之互動式的網站物件實際高達5,803筆,突破以往靜態少量網頁與物件的關鍵物件採掘,並且將研究中的網站物件分為資料型與功能型,透過本研究提出之多項語意定義與字串相似度比較法(Levenshtein Distance)進行比對,篩選出關鍵物件,以做為網站類型的配置依據,便於往後資料分析,並能節省網站製作成本,達成首頁自適性配置之目的。
For design and user inquirement of web, index page can be arranged automatically by according to that studies of key object mining (Velásquez et al., 2011) and three web pages types (Roth et al., 2010) .We used interactive data of 5,803 stories object data instead of few data of static web page and divided key object into function object and data object. We also used several semantic defines and Levenshtein Distance to find key object and analyzed the previous data to saving website design cost ,finally the goal is that website index page arranged automatically.