'An Artificial Immune System as a Recommender System for Web Sites'
Artificial Immune Systems have been used successfully to build recommender systems for film databases. In this research, an attempt is made to extend this idea to web site recommendation. A collection of more than 1000 individuals' web profiles (alternatively called preferences / favourites / b...
| Main Authors: | , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2002
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| Online Access: | https://eprints.nottingham.ac.uk/259/ |
| _version_ | 1848790381615906816 |
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| author | Morrison, Tom Aickelin, Uwe |
| author_facet | Morrison, Tom Aickelin, Uwe |
| author_sort | Morrison, Tom |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | Artificial Immune Systems have been used successfully to build recommender systems for film databases. In this research, an attempt is made to extend this idea to web site recommendation. A collection of more than 1000 individuals' web profiles (alternatively called preferences / favourites / bookmarks file) will be used. URLs will be classified using the DMOZ (Directory Mozilla) database of the Open Directory Project as our ontology. This will then be used as the data for the Artificial Immune Systems rather than the actual addresses. The first attempt will involve using a simple classification code number coupled with the number of pages within that classification code. However, this implementation does not make use of the hierarchical tree-like structure of DMOZ. Consideration will then be given to the construction of a similarity measure for web profiles that makes use of this hierarchical information to build a better-informed Artificial Immune System. |
| first_indexed | 2025-11-14T18:11:43Z |
| format | Conference or Workshop Item |
| id | nottingham-259 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T18:11:43Z |
| publishDate | 2002 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-2592021-05-31T14:47:41Z https://eprints.nottingham.ac.uk/259/ 'An Artificial Immune System as a Recommender System for Web Sites' Morrison, Tom Aickelin, Uwe Artificial Immune Systems have been used successfully to build recommender systems for film databases. In this research, an attempt is made to extend this idea to web site recommendation. A collection of more than 1000 individuals' web profiles (alternatively called preferences / favourites / bookmarks file) will be used. URLs will be classified using the DMOZ (Directory Mozilla) database of the Open Directory Project as our ontology. This will then be used as the data for the Artificial Immune Systems rather than the actual addresses. The first attempt will involve using a simple classification code number coupled with the number of pages within that classification code. However, this implementation does not make use of the hierarchical tree-like structure of DMOZ. Consideration will then be given to the construction of a similarity measure for web profiles that makes use of this hierarchical information to build a better-informed Artificial Immune System. 2002 Conference or Workshop Item PeerReviewed application/pdf en https://eprints.nottingham.ac.uk/259/1/02icaris_bookmark.pdf Morrison, Tom and Aickelin, Uwe (2002) 'An Artificial Immune System as a Recommender System for Web Sites'. In: 1st International Conference on ARtificial Immune Systems (ICARIS - 2002), 2002, Canterbury, UK. |
| spellingShingle | Morrison, Tom Aickelin, Uwe 'An Artificial Immune System as a Recommender System for Web Sites' |
| title | 'An Artificial Immune System as a Recommender System for Web Sites' |
| title_full | 'An Artificial Immune System as a Recommender System for Web Sites' |
| title_fullStr | 'An Artificial Immune System as a Recommender System for Web Sites' |
| title_full_unstemmed | 'An Artificial Immune System as a Recommender System for Web Sites' |
| title_short | 'An Artificial Immune System as a Recommender System for Web Sites' |
| title_sort | 'an artificial immune system as a recommender system for web sites' |
| url | https://eprints.nottingham.ac.uk/259/ |