Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.14279/9793| Title: | A dynamic Web Recommender System using Hard and Fuzzy K-modes clustering | Authors: | Christodoulou, Panayiotis Lestas, Marios Andreou, Andreas S. |
metadata.dc.contributor.other: | Χριστοδούλου, Παναγιώτης Ανδρέου, Ανδρέας Σ. |
Major Field of Science: | Engineering and Technology | Field Category: | Electrical Engineering - Electronic Engineering - Information Engineering | Keywords: | Hard and Fuzzy K-Modes clustering;Recommender Systems | Issue Date: | 1-Dec-2013 | Source: | 9th IFIP WG 12.5 International Conference on Artificial Intelligence Applications and Innovations, 2013, Paphos, Cyprus | DOI: | 10.1007/978-3-642-41142-7_5 | Conference: | IFIP WG 12.5 International Conference on Artificial Intelligence Applications and Innovations | 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: | https://hdl.handle.net/20.500.14279/9793 | ISBN: | 978-364241141-0 | Rights: | © IFIP International Federation for Information Processing 2013. | Type: | Conference Papers | Affiliation : | Cyprus University of Technology Frederick University |
Publication Type: | Peer Reviewed |
| Appears in Collections: | Δημοσιεύσεις σε συνέδρια /Conference papers or poster or presentation |
CORE Recommender
Items in KTISIS are protected by copyright, with all rights reserved, unless otherwise indicated.