2015
DOI: 10.17485/ijst/2015/v8i16/54252
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Information Extraction in Unstructured Multilingual Web Documents

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Cited by 10 publications
(5 citation statements)
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“…[12] After studying case studies, extensive literature reviews shows that there are lots of factors influencing cancer. [13] These factors are identified and taken as attributes for this study. [14] Wisconsin, USA [7] .…”
Section: Methodsmentioning
confidence: 99%
“…[12] After studying case studies, extensive literature reviews shows that there are lots of factors influencing cancer. [13] These factors are identified and taken as attributes for this study. [14] Wisconsin, USA [7] .…”
Section: Methodsmentioning
confidence: 99%
“…The TEI is transformed into an industry, thus began the unqualified faculty taking the teaching positions through fake degrees and fake credentials, as the manual verification is inefficient and corrupted shoving the TEI industry into a quagmire. The faculty credentials like qualifications and their degrees, courses learnt thorough MOOCs, professional memberships, research publications like (Prakash KB et al, 2015) (Prakash KB et al, 2016), patents, books written, consultancy services, conferences / seminars chaired and many other academic and financial credentials are placed in the blockchain as permanent records which are accessible to all the statutory bodies and potential employers. Thus avoiding fake faculty with faulty claims.…”
Section: B Faculty Credentialsmentioning
confidence: 99%
“…We are using Hyperparameter Optimization in this, which helps in creating to create models allows us to do a grid search. Here we used mtry, ntree, nodesize for best accuracy [15][16][17][18]. In R.F, not all the attributes are equally used in amount for classification and prediction [19][20][21].…”
Section: Gini Impurity = Entropy =mentioning
confidence: 99%