Conjunctive Query Answering in Rough EL

Rough Description Logics have recently been studied as a means for representing and reasoning with imprecise knowledge. Real-world applications need to exploit reasoning over such knowledge in an efficient way. We describe how the combined approach to query answering can be extended to the rough setting. In particular, we extend both the canonical model and the rewriting procedure such that rough queries over rough EL ontologies can be answered by considering this information alone

Los violadores y los que abusan de niños comparten un bajo nivel de actualización ejecutiva pero no de razonamiento fluido

Research findings suggest that sex offenders show worse performance than the general population in neuropsychological tests. Nevertheless, moderators such as age of the victim, use of antisocial control groups, and characteristics of administered measures have been highlighted. Here, 100 participants completed a battery of cognitive measures tapping fluid reasoning, verbal ability, and three basic executive processes (inhibition, switching, and updating). They were matched by educational level and classified in four groups: controls, non-sex offenders, rapists, and child abusers. The analyses revealed that rapists showed lower fluid reasoning scores than controls and child abusers. Furthermore, rapists and child abusers showed lower executive updating performance than controls and non-sex offenders. Importantly, child abusers did show fluid reasoning scores on a par with controls (controlling for updating differences), but their executive updating performance was equivalent to the one revealed by rapists (controlling for fluid intelligence differences). Implications of these findings for the design of efficient intervention programs are discussedLos datos de investigación empírica sugieren que los delincuentes sexuales presentan un peor desempeño que la población general en las pruebas neuropsicológicas. Aun así, se ha resaltado la influencia de variables moderadoras como la edad de la víctima, el uso de grupos control que incluyan individuos antisociales y las características de las medidas utilizadas. En este estudio cien participantes completaron una batería de pruebas cognitivas que evalúan razonamiento fluido, capacidad verbal y tres funciones ejecutivas básicas (inhibición, cambio y actualización). Los participantes estaban igualados en su nivel educativo y divididos en cuatro grupos: controles, delincuentes no sexuales, agresores sexuales con víctimas adultas y abusadores de menores. Los análisis revelaron que los agresores sexuales con víctimas adultas presentaban puntuaciones menores que los controles y los abusadores de menores en razonamiento fluido. Más aún, los agresores con víctimas adultas y los abusadores tenían peor desempeño que los controles y los delincuentes no sexuales en actualización ejecutiva. Es destacable que los abusadores de menores mostraran puntuaciones en razonamiento fluido equiparables a las de los controles (controlando estadísticamente las diferencias en actualización), pero su desempeño en actualización ejecutiva fue equivalente al mostrado por los agresores con víctimas adultas (controlando estadísticamente las diferencias en inteligencia fluida). Finalmente se discuten las implicaciones de estos resultados para el diseño de programas de intervención efectivo

Tractable approximate deduction for OWL

Acknowledgements This work has been partially supported by the European project Marrying Ontologies and Software Technologies (EU ICT2008-216691), the European project Knowledge Driven Data Exploitation (EU FP7/IAPP2011-286348), the UK EPSRC project WhatIf (EP/J014354/1). The authors thank Prof. Ian Horrocks and Dr. Giorgos Stoilos for their helpful discussion on role subsumptions. The authors thank Rafael S. Gonçalves et al. for providing their hotspots ontologies. The authors also thank BoC-group for providing their ADOxx Metamodelling ontologies.Peer reviewedPostprin

Converting Instance Checking to Subsumption: A Rethink for Object Queries over Practical Ontologies

Efficiently querying Description Logic (DL) ontologies is becoming a vital task in various data-intensive DL applications. Considered as a basic service for answering object queries over DL ontologies, instance checking can be realized by using the most specific concept (MSC) method, which converts instance checking into subsumption problems. This method, however, loses its simplicity and efficiency when applied to large and complex ontologies, as it tends to generate very large MSC's that could lead to intractable reasoning. In this paper, we propose a revision to this MSC method for DL SHI, allowing it to generate much simpler and smaller concepts that are specific-enough to answer a given query. With independence between computed MSC's, scalability for query answering can also be achieved by distributing and parallelizing the computations. An empirical evaluation shows the efficacy of our revised MSC method and the significant efficiency achieved when using it for answering object queries

Towards Log-Linear Logics with Concrete Domains

We present $\mathcal{MEL}^{++}$ (M denotes Markov logic networks) an extension of the log-linear description logics $\mathcal{EL}^{++}$-LL with concrete domains, nominals, and instances. We use Markov logic networks (MLNs) in order to find the most probable, classified and coherent $\mathcal{EL}^{++}$ ontology from an $\mathcal{MEL}^{++}$ knowledge base. In particular, we develop a novel way to deal with concrete domains (also known as datatypes) by extending MLN's cutting plane inference (CPI) algorithm.Comment: StarAI201