11. Analyzing Sensitivity of Answer Ordering Change
Ling Feng · 2017
Queries over probabilistic context databases result in probabilistic answers, which are often ranked according to certain ranking criteria. As the probabilities of the basic tuples may be imprecise and erroneous, and their perturbations may lead to great changes in answer ordering, sensitivity analysis like “Which basic probability change will make a certain element top-ranked?”, “Which basic probability change will swap the positions of the firstly and secondly ranked elements?”, and “To what extent the top-3 ranked results keep remaining at the top?” thus arise. This chapter categorizes ordering sensitivity questions into list-oriented or element-oriented, and formulates the sensitivity analysis problem for answer ordering returned from probabilistic top-k (aggregation) queries. A modular approach to quantitatively compute sensitivity of answer ordering is developed with five basic processing modules being identified. Optimization strategies are illustrated regarding each processing module for performance improvement.