🚀 go-pugleaf

              DEPARTMENT OF COMPUTER SCIENCE
                COLORADO STATE UNIVERSITY

                        BARNEY'S
               MONDAY AFTERNOON CLUB SEMINAR

	Speaker:	Joshua Alspector
			Dept of Electrical & Computer Engineering
			University of Colorado at Colorado Springs

	Date:		Friday, February 28, 1997
	     NOTE:  This is Friday, not Monday
	
	Time:		3:30 - 4:30 p.m.
	Place:		100 USC
	Host:		Chuck Anderson
			anderson@cs.colostate.edu
			(970) 491-7491

	Refreshments:  following the talk

FEATURE-BASED AND CLIQUE-BASED USER MODELS FOR MOVIE SELECTION

The huge amount of information available in the currently evolving 
world-wide information infrastructure at any one time can easily 
overwhelm end-users.  One way to address the information explosion 
is to use an "information filtering agent" which can select infor-
mation according to the interest and/or need of an end-user.  
However, at present few information filtering agents exist for the 
evolving world-wide multimedia information infrastructure.  In 
this study, we demonstrate the use of a feature-based neural 
network user model as the filtering agent for the video-on-demand 
application.  We evaluate the neural network approach for 10 
voluntary subjects who provided ratings for the movies.  Our 
preliminary results suggest that feature-based selection can 
be a useful tool to recommend movies according to the taste of 
the user and can be as effective as a movie rating expert.  We 
compare our feature-based approach with a clique-based approach, 
which has advantages where information from other users is available.