Please use this identifier to cite or link to this item: http://ktisis.cut.ac.cy/handle/10488/9793
Title: A dynamic Web Recommender System using Hard and Fuzzy K-modes clustering
Authors: Christodoulou, Panayiotis 
Lestas, Marios 
Andreou, Andreas S. 
Keywords: Hard and Fuzzy K-Modes clustering;Recommender Systems
Category: Electrical Engineering - Electronic Engineering - Information Engineering
Field: Engineering and Technology
Issue Date: 1-Dec-2013
Publisher: Springer
Source: 9th IFIP WG 12.5 International Conference on Artificial Intelligence Applications and Innovations, 2013, Paphos, Cyprus
metadata.dc.doi: 10.1007/978-3-642-41142-7_5
Abstract: This paper describes the design and implementation of a new dynamic Web Recommender System using Hard and Fuzzy K-modes clustering. The system provides recommendations based on user preferences that change in real time taking also into account previous searching and behavior. The recommendation engine is enhanced by the utilization of static preferences which are declared by the user when registering into the system. The proposed system has been validated on a movie dataset and the results indicate successful performance as the system delivers recommended items that are closely related to user interests and preferences.
URI: http://ktisis.cut.ac.cy/handle/10488/9793
ISBN: 978-364241141-0
Rights: © IFIP International Federation for Information Processing 2013.
Type: Conference Papers
Appears in Collections:Δημοσιεύσεις σε συνέδρια/Conference papers

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