"Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics 2012" . "Je\u017Eowicz, Tom\u00E1\u0161" . "2012-10-14+02:00"^^ . "[ABB432A8D12C]" . "10.1109/ICSMC.2012.6378021" . "Document classification is a well-known problem that is focused on assigning predefined labels or categories to the documents found in the searched collection. Many classical algorithms were developed for solving of this problem. They usually have large time complexity and with increasing number of documents it is necessary to find algorithm which are able to find solution in reasonable time. Such algorithms are usually inspired by biological processes. Even such meta-heuristics algorithms become too slow when the number of documents is really large and it is necessary to optimize them for faster processing. This paper describes a document classification algorithm based on Particle Swarm Optimization with implementation of one and two GPUs. 2012 IEEE."@en . "120538" . . "RIV/61989100:27740/12:86085008!RIV13-MSM-27740___" . "Soul" . . "Abraham Padath, Ajith" . . "A PSO-based document classification algorithm accelerated by the CUDA Platform"@en . . . . "New York" . . . . . "Plato\u0161, Jan" . "RIV/61989100:27740/12:86085008" . "978-1-4673-1714-6" . . "5"^^ . "Sn\u00E1\u0161el, V\u00E1clav" . . "IEEE" . "particle swarm optimization; optimization; gpu; document classification"@en . . "A PSO-based document classification algorithm accelerated by the CUDA Platform" . . . "Abraham Padath, Ajith" . "A PSO-based document classification algorithm accelerated by the CUDA Platform" . "P(ED1.1.00/02.0070), P(EE.2.3.20.0073), S" . . . . "4"^^ . "Kr\u00F6mer, Pavel" . . . "27740" . "6"^^ . "A PSO-based document classification algorithm accelerated by the CUDA Platform"@en . . "1062-922X" . . "Document classification is a well-known problem that is focused on assigning predefined labels or categories to the documents found in the searched collection. Many classical algorithms were developed for solving of this problem. They usually have large time complexity and with increasing number of documents it is necessary to find algorithm which are able to find solution in reasonable time. Such algorithms are usually inspired by biological processes. Even such meta-heuristics algorithms become too slow when the number of documents is really large and it is necessary to optimize them for faster processing. This paper describes a document classification algorithm based on Particle Swarm Optimization with implementation of one and two GPUs. 2012 IEEE." .