By Topic

Using Incomplete Fuzzy Linguistic Preference Relations to Characterize User Profiles in Recommender Systems

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Herrera-Viedma, E. ; Dept. of Comput. Sci. & A.I., Univ. of Granada, Granada, Spain ; Porcel, C.

We presented a fuzzy linguistic recommender system to advise research resources in university digital libraries. The problem of this system is that the user profiles are provided directly by the own users and the process for acquiring user preferences is quite difficult because it requires too much user effort. In this paper we present a new fuzzy linguistic recommender system that facilitates the acquisition of the user preferences to characterize the user profiles. We allow users to provide their preferences by means of an incomplete fuzzy linguistic preference relation. We include tools to manage incomplete information when the users express their preferences, and, in such a way, we show that the acquisition of the user profiles is improved.

Published in:

Intelligent Systems Design and Applications, 2009. ISDA '09. Ninth International Conference on

Date of Conference:

Nov. 30 2009-Dec. 2 2009