'On Affinity Measures for Artificial Immune System Movie Recommenders'
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...
| Main Authors: | , |
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| Format: | Conference or Workshop Item |
| Published: |
2004
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| Online Access: | https://eprints.nottingham.ac.uk/627/ |
| _version_ | 1848790448197337088 |
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| author | Aickelin, Uwe Chen, Qi |
| author_facet | Aickelin, Uwe Chen, Qi |
| author_sort | Aickelin, Uwe |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | 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. |
| first_indexed | 2025-11-14T18:12:46Z |
| format | Conference or Workshop Item |
| id | nottingham-627 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T18:12:46Z |
| publishDate | 2004 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-6272020-05-04T20:31:16Z https://eprints.nottingham.ac.uk/627/ 'On Affinity Measures for Artificial Immune System Movie Recommenders' Aickelin, Uwe Chen, Qi 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. 2004 Conference or Workshop Item PeerReviewed 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. |
| spellingShingle | Aickelin, Uwe Chen, Qi 'On Affinity Measures for Artificial Immune System Movie Recommenders' |
| title | 'On Affinity Measures for Artificial Immune System Movie Recommenders' |
| title_full | 'On Affinity Measures for Artificial Immune System Movie Recommenders' |
| title_fullStr | 'On Affinity Measures for Artificial Immune System Movie Recommenders' |
| title_full_unstemmed | 'On Affinity Measures for Artificial Immune System Movie Recommenders' |
| title_short | 'On Affinity Measures for Artificial Immune System Movie Recommenders' |
| title_sort | 'on affinity measures for artificial immune system movie recommenders' |
| url | https://eprints.nottingham.ac.uk/627/ |