'On Affinity Measures for Artificial Immune System Movie Recommenders'

Aickelin, Uwe and Chen, Qi (2004) 'On Affinity Measures for Artificial Immune System Movie Recommenders'. In: RASC-2004, The 5th International Conference on: Recent Advances in Soft Computing, 2004, Nottingham, UK.

Warning
There is a more recent version of this item available.
[thumbnail of 04rasc_ais.pdf] PDF - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
Download (61kB)

Abstract

Abstract. We combine Artificial Immune Systems (AIS) technology with Collaborative Filtering (CF) and use it to build a movie recommendation system. We already know that Artificial Immune Systems work well as movie recommenders from previous work by Cayzer and Aickelin ([3], [4], [5]). Here our aim is to investigate the effect of different affinity measure algorithms for the AIS. Two different affinity measures, Kendall's Tau and Weighted Kappa, are used to calculate the correlation coefficients for the movie recommender. We compare the results with those published previously and show that that Weighted Kappa is more suitable than others for movie problems. We also show that AIS are generally robust movie recommenders and that, as long as a suitable affinity measure is chosen, results are good.

Item Type: Conference or Workshop Item (Paper)
Schools/Departments: University of Nottingham, UK > Faculty of Science > School of Computer Science
Depositing User: Aickelin, Professor Uwe
Date Deposited: 07 Nov 2005
Last Modified: 31 May 2021 14:47
URI: https://eprints.nottingham.ac.uk/id/eprint/274

Available Versions of this Item

Actions (Archive Staff Only)

Edit View Edit View