In location-based services, a density query re- turns the regions with high concentrations of moving objects （MOs）. The use of density queries can help users identify crowded regions so as to avoid congestion. Most ...In location-based services, a density query re- turns the regions with high concentrations of moving objects （MOs）. The use of density queries can help users identify crowded regions so as to avoid congestion. Most of the exist- ing methods try very hard to improve the accuracy of query results, but ignore query efficiency. However, response time is also an important concern in query processing and may have an impact on user experience. In order to address this issue, we present a new definition of continuous density queries. Our approach for processing continuous density queries is based on the new notion of a safe interval, using which the states of both dense and sparse regions are dynamically main- tained. Two indexing structures are also used to index candi- date regions for accelerating query processing and improving the quality of results. The efficiency and accuracy of our approach are shown through an experimental comparison with snapshot density queries.展开更多
After a relation scheme R is decomposed into the set of schemes ρ={R_1,...,R_n},we may pose queries as if R existed in the database,taking a join of R_i's,when it is necessary to implement the query.Suppose a que...After a relation scheme R is decomposed into the set of schemes ρ={R_1,...,R_n},we may pose queries as if R existed in the database,taking a join of R_i's,when it is necessary to implement the query.Suppose a query involves a set of attributes S(?)R,we want to find the smallest subset of ρ whose union includes S.We prove that the problem is NP-complete and present a polynomial-bounded approximation algorithm.A subset of ρ whose union includes S and has a decomposition into 3NF with a lossless join and preservation of dependencies is given in the paper.展开更多
文摘In location-based services, a density query re- turns the regions with high concentrations of moving objects （MOs）. The use of density queries can help users identify crowded regions so as to avoid congestion. Most of the exist- ing methods try very hard to improve the accuracy of query results, but ignore query efficiency. However, response time is also an important concern in query processing and may have an impact on user experience. In order to address this issue, we present a new definition of continuous density queries. Our approach for processing continuous density queries is based on the new notion of a safe interval, using which the states of both dense and sparse regions are dynamically main- tained. Two indexing structures are also used to index candi- date regions for accelerating query processing and improving the quality of results. The efficiency and accuracy of our approach are shown through an experimental comparison with snapshot density queries.
文摘After a relation scheme R is decomposed into the set of schemes ρ={R_1,...,R_n},we may pose queries as if R existed in the database,taking a join of R_i's,when it is necessary to implement the query.Suppose a query involves a set of attributes S(?)R,we want to find the smallest subset of ρ whose union includes S.We prove that the problem is NP-complete and present a polynomial-bounded approximation algorithm.A subset of ρ whose union includes S and has a decomposition into 3NF with a lossless join and preservation of dependencies is given in the paper.
