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A Novel Large-scale Chinese Encyclopedia Knowledge Parallel Refining Method Based on MapReduce
2019
IEEE Access
The open collaborative characteristics of online encyclopedia and the large number of ambiguity phenomena in the encyclopedia entry lead to inappropriate classification of plenty of Infobox knowledge triples of entries, which requires for refining and denoising of large-scale knowledge to improve the precision of Knowledge Base (KB). The enormous amount of triples in the KBs will cause excessive serial computing time expenditure by knowledge denoising and disambiguation processing. Existing
doi:10.1109/access.2019.2934747
fatcat:trx4gu2elfga3g6y2uvoiukvoa