Uncertainty in big data analytics: survey, opportunities, and challenges

Journal of Big Data

Table 2 Uncertainty mitigation strategies

Artificial intelligence	Uncertainty	Mitigation
Machine learning	Incomplete training samples Inconsistent classification Learning from low veracity and noisy data	Active learning [65, 66], Deep learning [15, 63], Fuzzy sets [67], Feature selection [9, 60, 61]
	Learning from unlabeled data	Active learning [65, 66]
	Scalability	Distributed learning [12, 63] Deep learning [56]
Natural language processing	Keyword search	Fuzzy, Bayesian [68, 70, 71]
	Ambiguity of words in POS	ICA [73], LIBLINEAR and MNB algorithm [68]
	Classification (simplifying language assumption)	ICA [73], Open issue [68]
Computational intelligence	Low veracity, complex and noisy data	Fuzzy logic, EA [76, 79, 80, 82]
Computational intelligence	High volume, variety	Swarm intelligence, EA [78, 81, 82], Fuzzy-logic based matching algorithm, EA [81, 82]