Context aware filtering using social behavior of frogs

摘要: Abstract The problem of information overload surfaced with the emergent popularity dynamic web applications. To tackle this issue, various context awareness approaches have been developed to filter information. Conventional aware social filtering techniques predominantly focus on time and location as users. However, another relevant that user׳s demographic is often left out. paper presents based using behavior frogs. approach employs shuffled frog leaping algorithm (SFLA) perform modeling handle sparsity scalability issues in filtering. work proposes two distinct methodologies model – SFLA Contextual dimensional (SC2D) three (SC3D) approach. SC2D primarily develops a subsequently incorporates personal (occupation, gender, etc.) compute most items. In SC3D approach, amalgamated develop thereafter contextual used generate Experimental studies revealed able reduce error up 15% 8% compared MAC2D GAC2D, respectively, improves accuracy upto 31% respect MAC3D 26% GAC3D. Analysis variance (ANOVA) test results for all corroborate differences between means SC2D, GAC2D SC3D, GAC3D are highly significant. These improve confidence better optimization