Indexing Uncertain Categorical Data over Distributed Environment
نویسندگان
چکیده
Today, a large amount of uncertain data is produced by several applications where the management systems of traditional databases including indexing methods are not suitable to handle such type of data. In this paper, we propose an inverted based index method for efficiently searching uncertain categorical data over distributed environments. We address two kinds of query over the distributed uncertain databases, one a distributed probabilistic thresholds query, where all results satisfying the query with probabilities that meet a probabilistic threshold requirement are returned, and another a distributed top k-queries, where all results optimizing the transfer of the tuples and the time treatment are returned.
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