Probabilistic top-k and ranking query algorithms in uncertain databases
Yue Wu · Journal of Computer Applications · 2010
Processing and querying on uncertain and probabilistic data has emerged as a new research area in both databases and data mining communities due to the generation of a huge amount of such data in applications such as sensor networks and RFID technology.Both top-k query and ranking query are important and useful tools for analyzing the large collection of uncertain data.Various algorithms of probabilistic top-k and ranking query on uncertain data were introduced and reviewed.The semantics and application scenarios of different querying processing algorithms were analyzed.The computation cost and querying semantics of the existing probabilistic top-k and ranking queries were also compared.Finally,the challenges and possible research directions of uncertain databases querying and processing were presented.