<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Zhangquan Zhou</style></author><author><style face="normal" font="default" size="100%">Guilin Qi</style></author><author><style face="normal" font="default" size="100%">Chang Liu</style></author><author><style face="normal" font="default" size="100%">Raghava Mutharaju</style></author><author><style face="normal" font="default" size="100%">Pascal Hitzler</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Reasoning with Large Scale OWL 2 EL Ontologies Based on MapReduce</style></title><secondary-title><style face="normal" font="default" size="100%">Web Technologies and Applications - 18th Asia-Pacific Web Conference, APWeb 2016, Suzhou, China, September 23-25, 2016</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2016</style></year></dates><publisher><style face="normal" font="default" size="100%">Springer</style></publisher><pub-location><style face="normal" font="default" size="100%">Heidelberg</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Zhangquan Zhou</style></author><author><style face="normal" font="default" size="100%">Guilin Qi</style></author><author><style face="normal" font="default" size="100%">Chang Liu</style></author><author><style face="normal" font="default" size="100%">Pascal Hitzler</style></author><author><style face="normal" font="default" size="100%">Raghava Mutharaju</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Lluis Godo</style></author><author><style face="normal" font="default" size="100%">Henri Prade</style></author><author><style face="normal" font="default" size="100%">Guilin Qi</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Scale reasoning with fuzzy-EL+ ontologies based on MapReduce</style></title><secondary-title><style face="normal" font="default" size="100%">Proceedings of the IJCAI-2013 Workshop on Weighted Logics for Artificial Intelligence (WL4AI 2013)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2013</style></year></dates><pub-location><style face="normal" font="default" size="100%">Beijing, China</style></pub-location><pages><style face="normal" font="default" size="100%">87-93</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p class=&quot;rtejustify&quot;&gt;Fuzzy extension of Description Logics (DLs) allows the formal representation and handling of fuzzy or vague knowledge. In this paper, we consider the problem of reasoning with fuzzy-EL+, which is a fuzzy extension of EL+. We first identify the challenges and present revised completion classification rules for fuzzy-EL+ that can be handled by MapReduce programs. We then propose an algorithm for scale reasoning with fuzzy-EL+ ontologies using MapReduce. Some preliminary experimental results are provided to show the scalability of our algorithm.&lt;/p&gt;
</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>6</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Pascal Hitzler</style></author><author><style face="normal" font="default" size="100%">Markus Krötzsch</style></author><author><style face="normal" font="default" size="100%">Sebastian Rudolph</style></author></authors><subsidiary-authors><author><style face="normal" font="default" size="100%">Yong Yu</style></author><author><style face="normal" font="default" size="100%">Guilin Qi</style></author><author><style face="normal" font="default" size="100%">Haofen Wang</style></author><author><style face="normal" font="default" size="100%">Chang Liu</style></author></subsidiary-authors></contributors><titles><title><style face="normal" font="default" size="100%">语义Web技术基础</style></title></titles><dates><year><style  face="normal" font="default" size="100%">2013</style></year></dates><publisher><style face="normal" font="default" size="100%">Tsinghua University Press</style></publisher><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Zhangquan Zhou</style></author><author><style face="normal" font="default" size="100%">Guilin Qi</style></author><author><style face="normal" font="default" size="100%">Chang Liu</style></author><author><style face="normal" font="default" size="100%">Pascal Hitzler</style></author><author><style face="normal" font="default" size="100%">Raghava Mutharaju</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Luc De Raedt</style></author><author><style face="normal" font="default" size="100%">Christian Bessière</style></author><author><style face="normal" font="default" size="100%">Didier Dubois</style></author><author><style face="normal" font="default" size="100%">Patrick Doherty</style></author><author><style face="normal" font="default" size="100%">Paolo Frasconi</style></author><author><style face="normal" font="default" size="100%">Fredrik Heintz</style></author><author><style face="normal" font="default" size="100%">Peter J. F. Lucas</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Reasoning with Fuzzy-EL+ Ontologies Using MapReduce</style></title><secondary-title><style face="normal" font="default" size="100%">ECAI 2012 - 20th European Conference on Artificial Intelligence. Including Prestigious Applications of Artificial Intelligence (PAIS-2012) System Demonstrations Track</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2012</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.3233/978-1-61499-098-7-933</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">IOS Press</style></publisher><pub-location><style face="normal" font="default" size="100%">Montpellier, France</style></pub-location><volume><style face="normal" font="default" size="100%">242</style></volume><pages><style face="normal" font="default" size="100%">933–934</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p class=&quot;rtejustify&quot;&gt;Fuzzy extension of Description Logics (DLs) allows the formal representation and handling of fuzzy knowledge. In this paper, we consider fuzzy-EL+, which is a fuzzy extension of EL+. We first present revised completion rules for fuzzy-EL+ that can be handled by MapReduce programs. We then propose an algorithm for scale reasoning with fuzzy-EL+ ontologies based on MapReduce.&lt;/p&gt;
</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Yue Ma</style></author><author><style face="normal" font="default" size="100%">Guilin Qi</style></author><author><style face="normal" font="default" size="100%">Pascal Hitzler</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Computing Inconsistency Measure based on Paraconsistent Semantics</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of Logic and Computation</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2011</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1093/logcom/exq053</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">21</style></volume><pages><style face="normal" font="default" size="100%">1257–1281</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p class=&quot;rtejustify&quot;&gt;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: 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.&lt;/p&gt;
</style></abstract><issue><style face="normal" font="default" size="100%">6</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Yue Ma</style></author><author><style face="normal" font="default" size="100%">Guilin Qi</style></author><author><style face="normal" font="default" size="100%">Guohui Xiao</style></author><author><style face="normal" font="default" size="100%">Pascal Hitzler</style></author><author><style face="normal" font="default" size="100%">Zuoquan Lin</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Computational Complexity and Anytime Algorithm for Inconsistency Measurement</style></title><secondary-title><style face="normal" font="default" size="100%">International Journal of Software and Informatics</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">algorithm</style></keyword><keyword><style  face="normal" font="default" size="100%">computational complexity</style></keyword><keyword><style  face="normal" font="default" size="100%">inconsistency measurement</style></keyword><keyword><style  face="normal" font="default" size="100%">Knowledge representation</style></keyword><keyword><style  face="normal" font="default" size="100%">multi-valued logic</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2010</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ijsi.org/ch/reader/view_abstract.aspx?file_no=i41&amp;flag=1</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">4</style></volume><pages><style face="normal" font="default" size="100%">3–21</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p class=&quot;rtejustify&quot;&gt;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&lt;/p&gt;
</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Frank van Harmelen</style></author><author><style face="normal" font="default" size="100%">Andreas Herzig</style></author><author><style face="normal" font="default" size="100%">Pascal Hitzler</style></author><author><style face="normal" font="default" size="100%">Guilin Qi</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Preface - Special issue on commonsense reasoning for the semantic web</style></title><secondary-title><style face="normal" font="default" size="100%">Annals of Mathematics and Artificial Intelligence</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2010</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1007/s10472-010-9209-7</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">58</style></volume><pages><style face="normal" font="default" size="100%">1–2</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Yue Ma</style></author><author><style face="normal" font="default" size="100%">Guilin Qi</style></author><author><style face="normal" font="default" size="100%">Guohui Xiao</style></author><author><style face="normal" font="default" size="100%">Pascal Hitzler</style></author><author><style face="normal" font="default" size="100%">Zuoquan Lin</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Dimitris Karagiannis</style></author><author><style face="normal" font="default" size="100%">Zhi Jin</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">An Anytime Algorithm for Computing Inconsistency Measurement</style></title><secondary-title><style face="normal" font="default" size="100%">Knowledge Science, Engineering and Management, Third International Conference, KSEM 2009</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1007/978-3-642-10488-6_7</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">Springer</style></publisher><pub-location><style face="normal" font="default" size="100%">Vienna, Austria</style></pub-location><volume><style face="normal" font="default" size="100%">5914</style></volume><pages><style face="normal" font="default" size="100%">29–40</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p class=&quot;rtejustify&quot;&gt;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.&lt;/p&gt;
</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Qiu Ji</style></author><author><style face="normal" font="default" size="100%">Peter Haase</style></author><author><style face="normal" font="default" size="100%">Guilin Qi</style></author><author><style face="normal" font="default" size="100%">Pascal Hitzler</style></author><author><style face="normal" font="default" size="100%">Steffen Stadtmüller</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Lora Aroyo</style></author><author><style face="normal" font="default" size="100%">Paolo Traverso</style></author><author><style face="normal" font="default" size="100%">Fabio Ciravegna</style></author><author><style face="normal" font="default" size="100%">Philipp Cimiano</style></author><author><style face="normal" font="default" size="100%">Tom Heath</style></author><author><style face="normal" font="default" size="100%">Eero Hyvönen</style></author><author><style face="normal" font="default" size="100%">Riichiro Mizoguchi</style></author><author><style face="normal" font="default" size="100%">Eyal Oren</style></author><author><style face="normal" font="default" size="100%">Marta Sabou</style></author><author><style face="normal" font="default" size="100%">Elena Paslaru Bontas Simperl</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">RaDON - Repair and Diagnosis in Ontology Networks</style></title><secondary-title><style face="normal" font="default" size="100%">The Semantic Web: Research and Applications, 6th European Semantic Web Conference, ESWC 2009</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1007/978-3-642-02121-3_71</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">Springer</style></publisher><pub-location><style face="normal" font="default" size="100%">Heraklion, Crete, Greece</style></pub-location><volume><style face="normal" font="default" size="100%">5554</style></volume><pages><style face="normal" font="default" size="100%">863–867</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p class=&quot;rtejustify&quot;&gt;One of the major challenges in managing networked and dynamic ontologies is to handle inconsistencies in single ontologies, and inconsistencies introduced by integrating multiple distributed ontologies. Our RaDON system provides functionalities to repair and diagnose ontology networks by extending the capabilities of existing reasoners. The system integrates several new debugging and repairing algorithms, such as a relevance-directed algorithm to meet the various needs of the users.&lt;/p&gt;
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