Discovery of Shared Topics Networks among People - A Simple Approach to Find Community Knowledge from WWW Bookmarks

In this paper, we propose a system called kMedia that can assist users to form knowledge for community by showing shared topics networks (STN) among them. One of the important aspects to know each other is to know topics interested by others and relationship between her/his and others' topics. kMedia can use a simple but effective way to find them. It uses folders in WWW bookmarks as interested topics and can calculate their relations by evaluating similarity of WWW pages under folders. The results are displayed in two ways. One is to show relationship among users by shared topics networks, i.e., a user is connected to the other through both her/his topics and the other's topics that are related to her/his ones. A user can know what kind of relations to others s/he can have, and more precisely know what are counterpart of her/his topics for others. The other way is to show recommended pages for pages in users' bookmarks. Recommended pages are selected from others' b...

• Type: Conference
• Year: 2000
• Where: PRICAI
• Authors: Hideaki Takeda, Takeshi Matsuzuka, Yuichiro Taniguchi
• Keywords: Artificial Intelligence, Pages, PRICAI 2000, Recommended Pages, Shared Topics Networks