Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: An uncertain database is defined as a relational database in which primary keys need not be satisfied. A block is a maximal subset of tuples of the same relation that agree on the primary key. A repair (or possible world) of an uncertain database is obtained by selecting exactly one tuple from each block. From a probabilistic database perspective, an uncertain database is a restricted kind of block-independent disjoint (BID) probabilistic database, where the restriction is that the probabilities of tuples in a block are equal and sum up to one. For every fixed Boolean query q, the counting problem ♮CERTAINTY(q) takes as input an uncertain database db and asks to determine the number of repairs that satisfy q. A Boolean conjunctive query is self-join-free if no relation name occurs more than once in it. In previous work, it was proved that for every self-join-free Boolean conjunctive query q, the problem ♮CERTAINTY(q) is either in FP or ♮P-complete, and it is decidable which of the two cases applies. This complexity dichotomy has its analogue in BID probabilistic databases. The current paper investigates the complexity of the problem ♮CERTAINTY(q) for Boolean conjunctive queries with self-joins. Our most appealing result is that for every Boolean conjunctive query q (possibly with self-joins) in which all primary keys consist of a single attribute, ♮CERTAINTY(q) is either in FP or ♮P-complete, and it is decidable which of the two cases applies. Significantly, no analogous dichotomy for conjunctive queries with self-joins is known for BID probabilistic databases.
['Dany Maslowski', 'Jef Wijsen']
I am writing a research paper on a idea Counting Database Repairs that Satisfy Conjunctive Queries with Self-Joins.
[{"from": "human", "value": "I am writing a research paper on a idea Counting Database Repairs that Satisfy Conjunctive Queries with Self-Joins."}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: An uncertain database is defined as a relational database in which primary keys need not be satisfied. A block is a maximal subset of tuples of the same relation that agree on the primary key. A repair (or possible world) of an uncertain database is obtained by selecting exactly one tuple from each block. From a probabilistic database perspective, an uncertain database is a restricted kind of block-independent disjoint (BID) probabilistic database, where the restriction is that the probabilities of tuples in a block are equal and sum up to one. For every fixed Boolean query q, the counting problem \u266eCERTAINTY(q) takes as input an uncertain database db and asks to determine the number of repairs that satisfy q. A Boolean conjunctive query is self-join-free if no relation name occurs more than once in it. In previous work, it was proved that for every self-join-free Boolean conjunctive query q, the problem \u266eCERTAINTY(q) is either in FP or \u266eP-complete, and it is decidable which of the two cases applies. This complexity dichotomy has its analogue in BID probabilistic databases. The current paper investigates the complexity of the problem \u266eCERTAINTY(q) for Boolean conjunctive queries with self-joins. Our most appealing result is that for every Boolean conjunctive query q (possibly with self-joins) in which all primary keys consist of a single attribute, \u266eCERTAINTY(q) is either in FP or \u266eP-complete, and it is decidable which of the two cases applies. Significantly, no analogous dichotomy for conjunctive queries with self-joins is known for BID probabilistic databases."}]