Open Bookmark service based on self-adaptive information agents

Abstract

As the Web grows, the massive increase in information is placing severe burdens on information retrieval. Automated search engines and information directories with small editorial staff are unable to keep up with the increasing submissions of Web sites. To address the problem, this article introduces the Open Bookmark service based on self-adaptive information agents. One can record favorite URLs and easily manage them in the Web site. All the records are stored in a directory-tree, with different types of records in different directories. To perform information filtering, self-adaptive information agents are established to extract the user's profile from his bookmark records that represent his interests. This makes it possible for a personal and active information service. The agents are trained through interaction with the user so as to represent his interests more exactly. Open Bookmark service is also an open framework, in which information agents communicate with each other and exchange useful information. Thus the quality of information service can be greatly improved. Our application experiences show that Open Bookmark service is much more powerful than a conventional one.