Browsing is one of the most popular ways to gather information in database with hypertext structure. In the browsing, a user continuously searches nodes which include useful information for her/him. Her/his interests, then, often change while the browsing. We call this type of browsing “context-sensitive browsing” in order to distinguish it from browsing with consistent interests. In this paper, we propose a method to filter the links in hypertext based on the user's browsing history. We assume that even when a user browses, following changeable interests without a clear task, the user's current interests are reflected in the content and order of nodes in the browsing history. The filtering method models user's current interests from the user's browsing history and puts the next choices in order of the nearness to the interests. We call the filtering method “context-sensitive filtering”. We have developed a browsing support system with this method for an encyclopedia in CD-ROM format. The results of an experimental evaluation, by real users, are also reported.
[1]
Nicholas J. Belkin,et al.
Information filtering and information retrieval: two sides of the same coin?
,
1992,
CACM.
[2]
Peter Brusilovsky.
Methods and Techniques of Adaptive Hypermedia
,
1996
.
[3]
Pattie Maes,et al.
Agents that reduce work and information overload
,
1994,
CACM.
[4]
Yoav Shoham,et al.
Learning Information Retrieval Agents: Experiments with Automated Web Browsing
,
1995
.
[5]
Steven J. Plimpton,et al.
Massively parallel methods for engineering and science problems
,
1994,
CACM.
[6]
Peter Brusilovsky,et al.
Adaptive educational hypermedia: From ideas to real systems
,
1995
.
[7]
Ben Shneiderman,et al.
Designing The User Interface
,
2013
.
[8]
Henry Lieberman,et al.
Letizia: An Agent That Assists Web Browsing
,
1995,
IJCAI.
[9]
Thorsten Joachims,et al.
WebWatcher : A Learning Apprentice for the World Wide Web
,
1995
.
[10]
Robert C. Holte,et al.
A Learning Apprentice For Browsing
,
1994
.