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dc.date.accessioned 2009-10-09T12:24:09Z
dc.date.available 2009-10-09T03:00:00Z
dc.date.issued 2009-10
dc.identifier.uri http://sedici.unlp.edu.ar/handle/10915/9653
dc.description.abstract The very beginning of the research on Smart Adaptive Web Systems (SAWS). They are systems that adapt their response based on the context in which they are used. In AWS, three main sources of information have been identified are: user, environment, and technology. To design a site for adaptivity, the site s parts must be changeable according to users needs and interests. This paper represents a careful study of a large number of adaptive web systems which are used for adapting predesigned web pages and automatic synthesizing web pages. It suggests a new approach to extract the user s interest without the need of many visits to the web site or viewing the catalog in details. Different E-metrics are measured to evaluate the user s history, extract users interests, create adaptable interface, and synthesize a new page with special features referring to users needs and interests and also predict the next step the user may need. en
dc.format.extent 65-71 es
dc.language en es
dc.subject adaptivity en
dc.subject prediction en
dc.subject automatic synthesizing en
dc.title Hybrid approach for designing smart adaptive Web Sites en
dc.type Articulo es
sedici.identifier.uri http://journal.info.unlp.edu.ar/wp-content/uploads/JCST-Oct09-4.pdf es
sedici.identifier.issn 1666-6038 es
sedici.creator.person Kelash, Hamdey M. es
sedici.creator.person Koutb, Magdy M. es
sedici.creator.person Abu Al Kahir, Mona M. es
sedici.subject.materias Ciencias Informáticas es
sedici.description.fulltext true es
mods.originInfo.place Facultad de Informática es
sedici.subtype Articulo es
sedici.rights.license Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0)
sedici.rights.uri http://creativecommons.org/licenses/by-nc/3.0/
sedici.description.peerReview peer-review es
sedici2003.identifier ARG-UNLP-ART-0000005280 es
sedici.relation.journalTitle Journal of Computer Science & Technology es
sedici.relation.journalVolumeAndIssue vol. 9, no. 2 es


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Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0) Excepto donde se diga explícitamente, este item se publica bajo la siguiente licencia Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0)