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Application of a Hybrid Text Mining Approach to the Study of Suicidal Behavior in a Large Population

contributor authorHammond, K.W. , Laundry, R.J.
date accessioned2020-03-12T19:32:44Z
date available2020-03-12T19:32:44Z
date issued2014
identifier other6758921.pdf
identifier urihttps://libsearch.um.ac.ir:443/fum/handle/fum/981301?show=full
formatgeneral
languageEnglish
publisherIEEE
titleApplication of a Hybrid Text Mining Approach to the Study of Suicidal Behavior in a Large Population
typeConference Paper
contenttypeMetadata Only
identifier padid8095893
subject keywordsdata mining
subject keywordsfield programmable gate arrays
subject keywordsparallel processing
subject keywordsFPGA-based parallel system
subject keywordsFSM
subject keywordsHPC-gSpan system
subject keywordsdata mining
subject keywordsfield programmable gate array
subject keywordsfrequent subgraph mining
subject keywordsgboost library
subject keywordshigh performance computing
subject keywordsAcceleration
subject keywordsAlgorithm design and analysis
subject keywordsData mining
subject keywordsDatabases
subject keywordsReconfigurable logic
subject keywordsSoftware
subject keywordsSoftware algorithms
subject keywordsFrequent Subgraph Mining
subject keywordsHigh performance FPGA-based system
subject keywordsparallel algorihms
identifier doi10.1109/FPL.2014.6927441
journal titleystem Sciences (HICSS), 2014 47th Hawaii International Conference on
filesize178273
citations0


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