Corpus ID: 41896090

ectiveness Results for Popular e-Discovery Algorithms

@inproceedings{Yang2017ectivenessRF,
  title={ectiveness Results for Popular e-Discovery Algorithms},
  author={Eugene Yang and D. Grossman and O. Frieder and ophir grossman},
  year={2017}
}
E-Discovery applications rely upon binary text categorization to determine relevance of documents to a particular case. Although many such categorization algorithms exist, at present, vendors o‰en deploy tools that typically include only one text categorization approach. Unlike previous studies that vary many evaluation parameters simultaneously, fail to include common current algorithms, weights, or features, or use small document collections which are no longer meaningful, we systematically… Expand

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