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Automatically infer subject terms and documents associations through text mining
2013
Proceedings of the American Society for Information Science and Technology
Subject indexing is an intellectual intensive process that bears many inherent uncertainties. Existing subject index systems generally produce binary outcomes on whether assigning an indexing term or not, which does not sufficiently reflect to which extent the indexing terms are associated with documents. On the other hand, probabilistic models have seen great success in capturing the uncertainties in the automatic indexing process. One hurdle to achieving weighted indexing in manual subject
doi:10.1002/meet.14505001133
fatcat:xlcwpnrklrev3lm6bybcwgwdea