Публікація:
Adaptive Navigation Interface Powered by Evolutionary Algorithm

dc.contributor.authorFilatov, T.
dc.contributor.authorPopov, V.
dc.contributor.authorSakal, I.
dc.date.accessioned2016-09-06T11:01:10Z
dc.date.available2016-09-06T11:01:10Z
dc.date.issued2011
dc.description.abstractA combination of adaptive navigational interface and real time collaborative feedback analysis for documents relevance weighting is proposed as an viable alternative to prevailing ‘telegraphic’ approach in information retrieval systems. Adaptive navigation is provided through a dynamic links panel controlled by an evolutionary algorithm. Documents relevance is initially established with standard information retrieval techniques and is further refined in real time through interaction of users with the system. Introduced concepts of multidimensional Knowledge Map and Weighted Point of Interest allow finding relevant documents and users with common interests through a trivial calculation. Browsing search approach, the ability of the algorithm to adapt navigation to users interests, collaborative refinement and the self-organizing features of the system are the main factors making such architecture effective in various fields where nonstructured knowledge shall be represented to the users.uk_UA
dc.identifier.citationFilatov, T. Adaptive Navigation Interface Powered by Evolutionary Algorithm / T. Filatov, V. Popov, I. Sakalo // Радиоэлектроника и информатика : науч.-техн. журн. – Х. : Изд-во ХНУРЭ, 2011. – Вып. 4. – С. 64-75.uk_UA
dc.identifier.urihttp://openarchive.nure.ua/handle/document/2161
dc.language.isoenuk_UA
dc.publisherХНУРЭuk_UA
dc.subjectevolutionaryuk_UA
dc.subjectadaptiveuk_UA
dc.subjectnavigationuk_UA
dc.subjectwebuk_UA
dc.subjectcollaborativeuk_UA
dc.subjectsocialuk_UA
dc.subjectinterfaceuk_UA
dc.subjectinformation retrievauk_UA
dc.subjectknowledgeuk_UA
dc.subjectdocumentuk_UA
dc.subjectalgorithmuk_UA
dc.subjectadaptiveuk_UA
dc.subjecttextuk_UA
dc.subjectrefinementuk_UA
dc.titleAdaptive Navigation Interface Powered by Evolutionary Algorithmuk_UA
dc.typeArticleuk_UA
dspace.entity.typePublication

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