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| Titel: |
Selective dissemination of XML documents based on genetically learned user model and Support Vector Machines |
| Auteur: |
Srinivasa, K.G. Venugopal, K.R. Patnaik, L.M. |
| Verschenen in: |
Intelligent data analysis |
| Paginering: | Jaargang 11 (2007) nr. 5 pagina's 481-496 |
| Jaar: |
2007-10-16 |
| Inhoud: |
Extensible Markup Language (XML) has emerged as a medium for interoperability over the Internet. As the number of documents published in the form of XML is increasing, there is a need for selective dissemination of XML documents based on user interests. In the proposed technique, a combination of Adaptive Genetic Algorithms and multi class Support Vector Machine (SVM) is used to learn a user model. Based on the feedback from the users, the system automatically adapts to the user's preference and interests. The user model and a similarity metric are used for selective dissemination of a continuous stream of XML documents. Experimental evaluations performed over a wide range of XML documents, indicate that the proposed approach significantly improves the performance of the selective dissemination task, with respect to accuracy and efficiency. |
| Uitgever: |
IOS Press |
| Bronbestand: |
Elektronische Wetenschappelijke Tijdschriften |
Details van artikel 6 van 8 gevonden artikelen
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