Guilin Qi

Publications of Guilin Qi

• Preface - Special issue on commonsense reasoning for the semantic web.

  Authors: Frank van Harmelen, Andreas Herzig, Pascal Hitzler, Guilin Qi

  Ann. Math. Artif. Intell. 01/2010; 58:1-2.

• A Conflict-Based Operator for Mapping Revision.

  Authors: Guilin Qi, Qiu Ji, Peter Haase

  The Semantic Web - ISWC 2009, 8th International Semantic Web Conference, ISWC 2009, Chantilly, VA, USA, October 25-29, 2009. Proceedings; 01/2009

• A Distance-Based Operator to Revising Ontologies in DL SHOQ.

  Authors: Fangkai Yang, Guilin Qi, Zhisheng Huang

  Symbolic and Quantitative Approaches to Reasoning with Uncertainty, 10th European Conference, ECSQARU 2009, Verona, Italy, July 1-3, 2009. Proceedings; 01/2009

• A Relevance-Directed Algorithm for Finding Justifications of DL Entailments.

  Authors: Qiu Ji, Guilin Qi, Peter Haase

  The Semantic Web, Fourth Asian Conference, ASWC 2009, Shanghai, China, December 6-9, 2009. Proceedings; 01/2009

• RaDON - Repair and Diagnosis in Ontology Networks.

  Authors: Qiu Ji, Peter Haase, Guilin Qi, Pascal Hitzler, Steffen Stadtmüller

  The Semantic Web: Research and Applications, 6th European Semantic Web Conference, ESWC 2009, Heraklion, Crete, Greece, May 31-June 4, 2009, Proceedings; 01/2009

• A Kernel Revision Operator for Terminologies.

  Authors: Guilin Qi, Peter Haase, Zhisheng Huang, Jeff Z. Pan

  Proceedings of the 21st International Workshop on Description Logics (DL2008), Dresden, Germany, May 13-16, 2008; 01/2008

• A Modularization-Based Approach to Finding All Justifications for OWL DL Entailments.

  Authors: Boontawee Suntisrivaraporn, Guilin Qi, Qiu Ji, Peter Haase

  The Semantic Web, 3rd Asian Semantic Web Conference, ASWC 2008, Bangkok, Thailand, December 8-11, 2008. Proceedings; 01/2008

• A Kernel Revision Operator for Terminologies - Algorithms and Evaluation.

  Authors: Guilin Qi, Peter Haase, Zhisheng Huang, Qiu Ji, Jeff Z. Pan, Johanna Völker

  The Semantic Web - ISWC 2008, 7th International Semantic Web Conference, ISWC 2008, Karlsruhe, Germany, October 26-30, 2008. Proceedings; 01/2008

• A Segmentation-Based Approach for Approximate Query over Distributed Ontologies.

  Authors: Yimin Wang, Guilin Qi, Min Chen

  The Semantic Web, 3rd Asian Semantic Web Conference, ASWC 2008, Bangkok, Thailand, December 8-11, 2008. Proceedings; 01/2008

• An Algorithm for Computing Inconsistency Measurement by Paraconsistent Semantics.

  Authors: Yue Ma, Guilin Qi, Pascal Hitzler, Zuoquan Lin

  Symbolic and Quantitative Approaches to Reasoning with Uncertainty, 9th European Conference, ECSQARU 2007, Hammamet, Tunisia, October 31 - November 2, 2007, Proceedings; 01/2007

• Measuring Inconsistency for Description Logics Based on Paraconsistent Semantics.

  Authors: Yue Ma, Guilin Qi, Pascal Hitzler, Zuoquan Lin

  Symbolic and Quantitative Approaches to Reasoning with Uncertainty, 9th European Conference, ECSQARU 2007, Hammamet, Tunisia, October 31 - November 2, 2007, Proceedings; 01/2007

• Evaluating Formalisms for Modular Ontologies in Distributed Information Systems

  Authors: Yimin Wang, Jie Bao, Peter Haase, Guilin Qi

  01/2007

• An Anytime Algorithm for Computing Inconsistency Measurement

  Authors: Yue Ma, Guilin Qi, Guohui Xiao, Pascal Hitzler, Zuoquan Lin

  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 toMeasuring 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.

• Measuring Inconsistency in DL-Lite Ontologies

  Authors: Liping Zhou, Houkuan Huang, Guilin Qi, Yue Ma, Zhisheng Huang, Youli Qu

  Measuring Inconsistency in ontologies is an important topic in ontology engineering as it can provide extra information for dealing with inconsistency. Many approaches have been proposed to deal withMeasuring Inconsistency in ontologies is an important topic in ontology engineering as it can provide extra information for dealing with inconsistency. Many approaches have been proposed to deal with this issue. However, the main drawback of these algorithms is their high computational complexity. One of the main sources of the high complexity is the intractability of the underlying Description Logics (DLs). In this paper, we focus on an important tractable DL family, DL-Lite. We define an inconsistency degree of a DL-Lite ontology based on a three-valued semantics. We also present an algorithm to compute this inconsistency degree and show that its time-complexity is PTime in the size of ABox and TBox.

• Quasi-Classical Semantics for Expressive Description Logics

  Authors: Xiaowang Zhang, Guilin Qi, Yue Ma, Zuoquan Lin

  Inconsistency handling in expressive description logics is an important problem because inconsistency may naturally occur in an open world. In this paper, we first present the quasi-classicalInconsistency handling in expressive description logics is an important problem because inconsistency may naturally occur in an open world. In this paper, we first present the quasi-classical semantics for description logic SHIQ, which is based on quasi-classical logic. We show that this semantics can be used to deal with inconsistency and that it is reduced to the standard semantics when there is no inconsistency. Compared with the existing four-valued semantics for description logics, it strengthens the reasoning capability in the sense that it can satisfy some important inference rules, such as Modus Ponens. Finally, we analyze the computational complexity of consistency checking based on the quasi-classical semantics.

• Computing Inconsistency Measure based on Paraconsistent Semantics

  Authors: Yue Ma, Guilin Qi, Pascal Hitzler

  Journal of Logic and Computation.

  Measuring inconsistency in knowledge bases has been recog- nized as an important problem in several research areas. Many methods have been proposed to solve this problem and a main class of them isMeasuring inconsistency in knowledge bases has been recog- nized 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: 1) They are mostly restricted to propositional knowledge bases; 2) Very few of them discuss computational aspects of computing inconsistency measures. In this paper, 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.

• Computational Complexity and Anytime Algorithm for Inconsistency Measurement

  Authors: Yue Ma, Guilin Qi, Guohui Xiao, Pascal Hitzler, Zuoquan Lin

  Int. J. Software and Informatics.

  Measuring inconsistency degrees of inconsistent knowledge bases is an important problem as it provides context information for facilitating inconsistency handling. Many methods have been pro- posedMeasuring inconsistency degrees of inconsistent knowledge bases is an important problem as it provides context information for facilitating inconsistency handling. Many methods have been pro- posed 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.

• Computing Inconsistency Measurements under Multi-Valued Semantics by Partial Max-SAT Solvers

  Authors: Guohui Xiao, Zuoquan Lin, Yue Ma, Guilin Qi

  Twelfth International Conference on the Principles of Knowledge Representation and Reasoning (KR).

  Measuring the inconsistency degree of a knowledge base can help us to deal with inconsistencies. Several inconsistency measures have been given under different multi-valued semantics, includingMeasuring the inconsistency degree of a knowledge base can help us to deal with inconsistencies. Several inconsistency measures have been given under different multi-valued semantics, including 4-valued semantics, 3-valued semantics, LPm and Quasi Classical semantics. In this paper, we first carefully analyze the relationship between these inconsistency measures by showing that the inconsistency degrees under 4-valued semantics, 3-value semantics, LPm are the same, but different from the one based on Quasi Classical semantics. We then consider the computation of these inconsistency measures and show that computing inconsistency measurement under multi-valued semantics is usually intractable. To tackle this problem, we propose two novel algorithms that respectively encode the problems of computing inconsistency degrees under 4-valued semantics (3-valued semantics, LPm) and under Quasi Classical semantics into the partial Max-SAT problems. We implement these algorithms and do experiments on some benchmark data sets. The preliminary but encouraging experimental results show that our approach is efficient to handle large knowledge bases.