Let’s browse: a collaborative browsing agent
H. Lieberman
*
, N. van Dyke, A. Vivacqua
Media Laboratory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
Received 1 June 1999; accepted 18 June 1999
Abstract
Web browsing, like most of today’s desktop applications, is usually a solitary activity. Other forms of media, such as watching television,
are often done by groups of people, such as families or friends. What would it be like to do collaborative Web browsing? Could the computer
provide assistance to group browsing by trying to help find mutual interests among the participants? Let’s Browse is an experiment in
building an agent to assist a group of people in browsing, by suggesting new material likely to be of common interest. It is built as an
extension to the single user Web browsing agent Letizia. Let’s Browse features automatic detection of the presence of users, automated
“channel surfing” browsing, and dynamic display of the user profiles and explanation of recommendations. ᭧1999 Elsevier Science B.V. All
rights reserved.
Keywords: Browsing; Collaboration; Agents; User profiles
1. Collaborative browsing
Increasingly, Web browsing will be performed in colla-
borative settings, such as a family at home or in a business
meeting. For example, WebTV estimates that the average
number of people who are watching during a session with its
service is two, indicating that multi-user browsing is the
norm rather than the exception. In most such situations,
one person has control of the remote or the keyboard and
mouse, and the others present are relatively passive. Yet the
browsing session cannot be considered successful if the
interests of others present are not taken into account.
Collaborative browsing can take many forms. A group of
people may be searching for specific information, exploring
previously unexplored territory to see what is interesting, or
some combination of the two. What links a person chooses
to view and how a person reacts to what appears can also
serve as a meaningful form of communication between the
participants. Participants can learn about each other as well
as learn about the content of the Web pages.
Increasingly, also, we believe that Web browsing will
be assisted by intelligent agent software, which can
keep track of user’s interests, inferring interest from
observing user actions, and autonomously looking for
items that satisfy interests. We have had extensive
experience with such a single-user agent, Letizia [1,2],
which performs reconnaissance on Web pages. Letizia
proactively fetches links from the page currently viewed,
and chooses those pages that best match a user profile
learned by watching the user’s choices. Letizia presents its
recommendations in a separate, “channel surfing” window
that continuously displays recommendations.
We were interested in extending the channel surfing
metaphor to situations where, as in TV, more than one
person may be watching. Even if only person “has the
remote control”, the agent can be cast in the role of repre-
senting the interests of the other participants, without requir-
ing negotiation at every step, which may be disruptive. The
job of the agent is to choose, from the links reachable from
the current page, those that are likely to best satisfy the
interests of all the participants. We call the resulting system
Let’s Browse.
2. Communityware: agents meet groupware
Let’s Browse is part of a growing trend towards commu-
nityware—software that enhances the formation, mainte-
nance and functioning of digital communities.
Traditionally, the field of Computer Supported Cooperative
Work, or CSCW [3] has been the forum for studying soft-
ware that is used by groups of more than one person working
together. However, the focus in CSCW is on making shared
desktop applications and communication technologies such
asvideo conferencing.Therole thatthecomputer playsin this
interaction is really that of a communication and recording
Knowledge-Based Systems 12 (1999) 427–431
0950-7051/99/$ - see front matter ᭧ 1999 Elsevier Science B.V. All rights reserved.
PII: S0950-7051(99)00036-2
* Corresponding author.
E-mail address: lieber@media.mit.edu (H. Lieberman)
www.elsevier.com/locate/knosys