Applying Web Mining to Personalization of Web Browsing—A Case Study in the Health Examination Industry

• Main Authors: Ya-Hui Huang, 黃雅慧
• Other Authors: Ching-Ming Chao
• Format: Others
• Language: zh-TW
• Published: 2003
• Online Access: http://ndltd.ncl.edu.tw/handle/29394332378672671613

碩士 === 東吳大學 === 資訊科學系 === 91 === Nowadays, in the prosperous era of Internet, people usually use the Internet for accessing the information they need. Because different users may have different needs, personalization of web browsing has become the trend for running a web site. A web site will be designed with the specific contents and relevant information that meet individual user’s need and will establish a one-to-one relationship with customers. Logs on a web site keep track of browsing records of the user and conceal the user’s de-mand on information. The subject of this study is on health examination in the medical care industry. By utilizing data mining techniques on web logs, we can find out the pattern in which users access web pages. Although the number of accessing a web page is an important consideration, the duration in which a person browses the web page really reveals the extent a user concerns about the web page. Therefore, in order to achieve personalization of web browsing, we propose an association rule algorithm to discover the association between web pages. This algorithm uses duration on web pages as the weighted support and is called the WS algorithm. In addition, by combining web logs and membership data, we utilize the deci-sion-tree function of PolyAnalyst to classify the characteristics and browsing behavior of us-ers. Personalization of web browsing not only can provide the user with fast access to the re-quired information, but also can help the health examiner to improve the design of the struc-ture of web pages and propose an effective advertisement.