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Big Graph Analyses: From Queries to Dependencies and Association Rules
2017
Data Science and Engineering
This position paper provides an overview of our recent advances in the study of big graphs, from theory to systems to applications. We introduce a theory of bounded evaluability, to query big graphs by accessing a bounded amount of the data. Based on this, we propose a framework to query big graphs with constrained resources. Beyond queries, we propose functional dependencies for graphs, to detect inconsistencies in knowledge bases and catch spams in social networks. As an example application
doi:10.1007/s41019-016-0025-x
fatcat:xrvufreijrhuzc77kaiancubxm