Spark: top-k keyword query in relational databases
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
BLINKS: ranked keyword searches on graphs
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
Effective keyword search for valuable lcas over xml documents
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Efficiently Answering Probabilistic Threshold Top-k Queries on Uncertain Data
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
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Nowadays a huge amount of data were automatically generated or extracted from other data sources. The uncertainty and imprecision are intrinsic in those data. In this paper, we study the problem of effective keyword search over uncertain data. We allow approximate matching between input keywords and the strings in the underlying data, even in the presence of minor errors of input keywords. We formalize the problem of fuzzy keyword search over uncertain data. We propose efficient algorithms, effective ranking functions, and early-termination techniques to facilitate fuzzy keyword search over uncertain data. We propose a lattice based fuzzy keyword search method to efficiently identify top-k answers. Extensive experiments on a real dataset show that our proposed algorithm achieves both high result quality and search efficiency.