🚀 go-pugleaf

              DEPARTMENT OF COMPUTER SCIENCE
                 COLORADO STATE UNIVERSITY

                        BARNEY'S
               MONDAY AFTERNOON CLUB SEMINAR


	Speaker:  Professor Joshua Alspector
	          Dept. Electrical and Computer Engineering
	          University of Colorado at Colorado Springs

	   Date:  Friday, November 15, 1996
		  [NOTE:  NOT MONDAY]

	   Time:  3:30 p.m.
	  Place:  100 USC

	     Refreshments:  following the talk

	     Host:  Check Anderson, 491-7491
	            anderson@cs.colostate.edu

        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 information 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 net-
  work 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.