@article {1651,
title = {Computing Inconsistency Measure based on Paraconsistent Semantics},
year = {2011},
abstract = {Measuring inconsistency in knowledge bases has been recognized as an important problem in several research areas. Many methods have been proposed to solve this problem and a main class of them is based on some kind of paraconsistent semantics. However, existing methods suffer from two limitations: (i) they are mostly restricted to propositional knowledge bases; (ii) very few of them discuss computational aspects of computing inconsistency measures. In this article, we try to solve these two limitations by exploring algorithms for computing an inconsistency measure of first-order knowledge bases. After introducing a four-valued semantics for first-order logic, we define an inconsistency measure of a first-order knowledge base, which is a sequence of inconsistency degrees. We then propose a precise algorithm to compute our inconsistency measure. We show that this algorithm reduces the computation of the inconsistency measure to classical satisfiability checking. This is done by introducing a new semantics, named S[n]-4 semantics, which can be calculated by invoking a classical SAT solver. Moreover, we show that this auxiliary semantics also gives a direct way to compute upper and lower bounds of inconsistency degrees. That is, it can be easily revised to compute approximating inconsistency measures. The approximating inconsistency measures converge to the precise values if enough resources are available. Finally, by some nice properties of the S[n]-4 semantics, we show that some upper and lower bounds can be computed in P-time, which says that the problem of computing these approximating inconsistency measures is tractable.},
author = {Yue Ma and Guilin Qi and Pascal Hitzler}
}
@article {874,
title = {Computational Complexity and Anytime Algorithm for Inconsistency Measurement},
journal = {International Journal of Software and Informatics},
year = {2010},
pages = {3-21},
abstract = {Measuring inconsistency degrees of inconsistent knowledge bases is an important problem as it provides context information for facilitating inconsistency handling. Many methods have been proposed to solve this problem and a main class of them is based on some kind of paraconsistent semantics. In this paper, we consider the computational aspects of inconsistency degrees of propositional knowledge bases under 4-valued semantics. We first give a complete analysis of the computational complexity of computing inconsistency degrees. As it turns out that computing the exact inconsistency degree is intractable, we then propose an anytime algorithm that provides tractable approximations of the inconsistency degree from above and below. We show that our algorithm satisfies some desirable properties and give experimental results of our implementation of the algorithm. },
keywords = {algorithm, computational complexity, inconsistency measurement, multi-valued logic},
author = {Yue Ma and Guilin Qi and Guohui Xiao and Pascal Hitzler and Zuoquan Lin}
}
@conference {916,
title = {An Anytime Algorithm for Computing Inconsistency Measurement},
booktitle = {Third International Conference, KSEM 2009},
year = {2009},
abstract = {Measuring inconsistency degrees of inconsistent knowledge bases is an important problem as it provides context information for facilitating inconsistency handling. Many methods have been proposed to solve this problem and a main class of them is based on some kind of paraconsistent semantics. In this paper, we consider the computational aspects of inconsistency degrees of propositional knowledge bases under 4-valued semantics. We first analyze its computational complexity. As it turns out that computing the exact inconsistency degree is intractable, we then propose an anytime algorithm that provides tractable approximation of the inconsistency degree from above and below.We show that our algorithm satisfies some desirable properties and give experimental results of our implementation of the algorithm.},
author = {Yue Ma and Guilin Qi and Guohui Xiao and Zuoquan Lin and Pascal Hitzler}
}
@conference {990,
title = {A Forgetting-based Approach for Handling Inconsistency in Distributed Ontologies},
year = {2008},
publisher = {5th European Semantic Web Conference, ESWC08},
organization = {5th European Semantic Web Conference, ESWC08},
abstract = {In the context of multiple distributed ontologies, we are often confronted with the problem of dealing with inconsistency. In this paper, we propose an approach for reasoning with inconsistent distributed ontologies based on *concept forgetting*.We firstly define *concept forgetting* in description logics.We then adapt the notions of recoveries and preferred recoveries in propositional logic to description logics. Two consequence relations are then defined based on the preferred recoveries.},
author = {Guilin Qi and Yimin Wang and Peter Haase and Pascal Hitzler}
}
@conference {940,
title = {An Algorithm for Computing Inconsistency Measurement by Paraconsistent Semantics},
booktitle = {Proceedings of Ninth European Conference on Symbolic and Quanlitative Approaches to Reasoning with Uncertainty},
year = {2007},
pages = {91-102},
address = {Hammamet,Tunisia},
abstract = {Measuring inconsistency in knowledge bases has been recognized as an important problem in many research areas. Most of approaches proposed for measuring inconsistency are based on paraconsistent semantics. However, very few of them provide an algorithm for implementation. In this paper, we first give a four-valued semantics for first-order logic and then propose an approach for measuring the degree of inconsistency based on this four-valued semantics. After that, we propose an algorithm to compute the inconsistency degree by introducing a new semantics for first order logic, which is called S[n]-4 semantics.},
author = {Yue Ma and Guilin Qi and Zuoquan Lin and Pascal Hitzler}
}
@conference {941,
title = {Measuring Inconsistency for Description Logics Based on Paraconsistent Semantics},
booktitle = {Ninth European Conference on Symbolic and Quanlitative Approaches to Reasoning with Uncertainty},
year = {2007},
address = {Hammamet, Tunisia},
abstract = {In this paper, we present an approach for measuring inconsistency in a knowledge base.We first define the degree of inconsistency using a four-valued semantics for the description logic ALC. Then an ordering over knowledge bases is given by considering their inconsistency degrees. Our measure of inconsistency can provide important information for inconsistency handling.},
author = {Yue Ma and Guilin Qi and Zuoquan Lin and Pascal Hitzler}
}
@conference {995,
title = {Measuring Inconsistency for Description Logics Based on Paraconsistent Semantics},
year = {2007},
publisher = {the 2007 International Workshop on Description Logics (DL-2007)},
organization = {the 2007 International Workshop on Description Logics (DL-2007)},
abstract = {In this paper, we present an approach for measuring inconsistency in a knowledge base.We first define the degree of inconsistency using a four-valued semantics for the description logic ALC. Then an ordering over knowledge bases is given by considering their inconsistency degrees. Our measure of inconsistency can provide important information for inconsistency handling.},
author = {Yue Ma and Guilin Qi and Pascal Hitzler and Zuoquan Lin}
}