Catching Numeric Inconsistencies in Graphs
Wenfei Fan, Xueli Liu, Ping Lü, Chao Tian · 2018
Numeric inconsistencies are common in real-life knowledge bases and social networks. To catch such errors, we propose to extend graph functional dependencies with linear arithmetic expressions and comparison predicates, referred to as NGDs. We study fundamental problems for NGDs. We show that their satisfiability, implication and validation problems are Σ 2 p-complete, ¶II2 p-complete and coNP-complete, respectively. However, if we allow non-linear arithmetic expressions, even of degree at most 2, the satisfiability and implication problems become undecidable. In other words, NGDs strike a balance between expressivity and complexity.