Meaningless to meaningful Web log data for generation of Web pre-caching decision rules using Rough Set
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F12%3A86092940" target="_blank" >RIV/61989100:27240/12:86092940 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1109/DMO.2012.6329804" target="_blank" >http://dx.doi.org/10.1109/DMO.2012.6329804</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/DMO.2012.6329804" target="_blank" >10.1109/DMO.2012.6329804</a>
Alternative languages
Result language
angličtina
Original language name
Meaningless to meaningful Web log data for generation of Web pre-caching decision rules using Rough Set
Original language description
Web caching and pre-fetching are vital technologies that can increase the speed of Web loading processes. Since speed and memory are crucial aspects in enhancing the performance of mobile applications and websites, a better technique for Web loading process should be investigated. The weaknesses of the conventional Web caching policy include meaningless information and uncertainty of knowledge representation in Web logs data from the proxy cache to mobile-client. The organisation and learning task of the knowledge-processing for Web logs data require explicit representation to deal with uncertainties. This is due to the exponential growth of rules for finding a suitable knowledge representation from the proxy cache to the mobileclient. Consequently, Rough Set is chosen in this research to generate Web pre-caching decision rules to ensure the meaningless Web log data can be changed to meaningful information. 2012 IEEE.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2012
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Conference on Data Mining and Optimization 2012
ISBN
978-1-4673-2718-3
ISSN
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e-ISSN
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Number of pages
8
Pages from-to
91-98
Publisher name
IEEE
Place of publication
New York
Event location
Langkawi
Event date
Oct 2, 2012
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000310354100016