Unloading Unwanted Information: From Physical Websites to Personalized Web Views
Conference Proceeding Article
With the explosion of information on the Web, information that is made available from websites is generally overwhelming to users surfing the sites. The majority of the users who are facing this information overloading problem are the ordinary home users who do not have much technical knowledge. It is thus important to allow these users to easily create personalized views of websites such that they only see what they want in the way they prefer. In this paper, we propose the concept of a personalized Web view to cater to this requirement. Underlying this concept is a data model that represents websites from the logical point of view and a declarative langauge that transforms logical views into personalized Web views. To empower ordinary users with the ability to build their own personalized Web views, we have designed and implemented a software system, known as WICCAP. This system includes a wizard to help users create data models that map physical websites into logical views. It also has. an information extraction agent that allows users to instantiate their personalized Web views of the target websites by transforming from logical views previously defined. In order to increase the fun and flexibility of using this software, a flexible presentation toolkit has been designed to present the information in a manner that is programmable by the users.
Data models, User behavior, User assistance, Software architecture, Overload, World wide web, Software tool, Information extraction, Software development, Internet
Databases and Information Systems | Numerical Analysis and Scientific Computing
Data Management and Analytics
Sixth Asia Pacific Web Conference (APWeb 2004)
City or Country
Hangzhou, China, Apr 14-17
LIU, Zehua; NG, Wee-Keong; LIM, Ee Peng; Huang, Yangfeng; and LI, Feifei.
Unloading Unwanted Information: From Physical Websites to Personalized Web Views. (2004). Sixth Asia Pacific Web Conference (APWeb 2004). 3007, 111-121. Research Collection School Of Information Systems.
Available at: http://ink.library.smu.edu.sg/sis_research/889