| dc.creator (作者) | 楊亨利;林青峰 | zh_TW |
| dc.date (日期) | 2006-10 | en_US |
| dc.date.accessioned | 17-Jan-2009 16:05:11 (UTC+8) | - |
| dc.date.available | 17-Jan-2009 16:05:11 (UTC+8) | - |
| dc.date.issued (上傳時間) | 17-Jan-2009 16:05:11 (UTC+8) | - |
| dc.identifier.uri (URI) | https://nccur.lib.nccu.edu.tw/handle/140.119/27044 | - |
| dc.description.abstract (摘要) | 客戶在從事消費時，往往會有許多不一樣的行為產生。對組織而言，研究客戶的消費行為能夠協助組織更了解客戶的資訊，進而支援其經苦活動。以往與客戶行為相關的資料挖掘研究，較著重於客戶的消費資料。而對於客戶在商店中做了那些動作，及其動作會導致發生的事件並沒有較全盤及深入的討論。對實體業者而言，要實際的去記錄使用者在商店內的行為，是不太可行的;但從另一個層面來說，隨著網際網路與資料收集技術的發展，網站經告者應用 log 留存技術，將比傳統業者更容易且完整的收集到消費者行為記錄。本研究試圖在全球資訊網的環境中建立一個能夠同時分析使用者的瀏覽網頁路徑及其動作過程的演算法;並且配合該演算法建置一個雛形系統，以驗証其效能，最後並評估其日後實務操作的可行性。 The purchasing behaviors of different customers are various. The study of customer purchasing behavior can help organizations understand their client intentions to support their business activities. In the past, customer behavior data mining emphasized on the purchase items, i.e., what customers buy. There were few studies discussing what paths they took and what actions they made in an e-store. It is impossible for a physical store to record its customers` all actions and passing paths. However, a website store can easily collect such data in an Internet log. This study proposes a data mining algorithm that can analyze both customers` browsing pages and their actions paths. The algorithm`s efficiency and feasibility were examined in our prototype. This study would contribute to help the website mangers to restructure their website layouts or advertisement position to catch the customer`s eyes. | - |
| dc.format | application/pdf | en_US |
| dc.format.extent | 975445 bytes | - |
| dc.format.mimetype | application/pdf | - |
| dc.language | zh-TW | en_US |
| dc.language | en-US | en_US |
| dc.language.iso | en_US | - |
| dc.relation (關聯) | 資訊管理學報, 13(4), 27-52 | en_US |
| dc.subject (關鍵詞) | 全球資訊網;網站使用挖掘;資料挖掘;使用者行為;網頁路徑;動作路徑;World-wide-web;Web-usage Mining;Data-mining;User Behavior;Page Path;Action Path | - |
| dc.title (題名) | 全球資訊網中網頁-動作使用路徑的資料挖掘 | zh_TW |
| dc.type (資料類型) | article | en |
