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The data warehouse maintains huge set of relational data bases and provides access to vast users of the external world. As the database contains various information which are more sensitive in different aspects, maintaining the security and integrity of the databases becomes a challenging issue. There are number of methods has been discussed for the problem of integrity management in data warehouses, but suffers to achieve the security performance. To overcome the deficiency of previous methods, an multi level multi attribute relational trust measure based approach. The method maintains the relational objects under different hierarchy and for each hierarchy there are number of relational objects and properties covered. Also the method maintains the trace about the earlier access of the users with relational data profile. Based on the relational data profile, the method computes the trust measure for the user. Computed multi level multi attribute trust measure is used to restrict the user and maintain the integrity of data objects. The method produces efficient results in integrity management and produces less time complexity.
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 1 | |
popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |