RORS: Enhanced Rule-based OWL Reasoning on Spark

The rule-based OWL reasoning is to compute the deductive closure of an ontology by applying RDF/RDFS and OWL entailment rules. The performance of the rule-based OWL reasoning is often sensitive to the rule execution order. In this paper, we present an approach to enhancing the performance of the rule-based OWL reasoning on Spark based on a locally optimal executable strategy. Firstly, we divide all rules (27 in total) into four main classes, namely, SPO rules (5 rules), type rules (7 rules), sameAs rules (7 rules), and schema rules (8 rules) since, as we investigated, those triples corresponding to the first three classes of rules are overwhelming (e.g., over 99% in the LUBM dataset) in our practical world. Secondly, based on the interdependence among those entailment rules in each class, we pick out an optimal rule executable order of each class and then combine them into a new rule execution order of all rules. Finally, we implement the new rule execution order on Spark in a prototype called RORS. The experimental results show that the running time of RORS is improved by about 30% as compared to Kim & Park's algorithm (2015) using the LUBM200 (27.6 million triples).Comment: 12 page

Merging plans with incomplete knowledge about actions and goals through an agent-based reputation system

In This Paper, We Propose And Compare Alternative Ways To Merge Plans Formed Of Sequences Of Actions With Unknown Similarities Between The Goals And Actions. Plans Are Formed Of Actions And Are Executed By Several Operator Agents, Which Cooperate Through Recommendations. The Operator Agents Apply The Plan Actions To Passive Elements (Which We Call Node Agents) That Will Require Additional Future Executions Of Other Plans After Some Time. The Ignorance Of The Similarities Between The Plan Actions And The Goals Justifies The Use Of A Distributed Recommendation System To Produce A Useful Plan For A Given Operator Agent To Apply Towards A Certain Goal. This Plan Is Generated From The Known Results Of Previous Executions Of Various Plans By Other Operator Agents. Here, We Present The General Framework Of Execution (The Agent System) And The Results Of Applying Various Merging Algorithms To This Problem.This work was supported in part by Project MINECO TEC2017-88048-C2-2-

Extensión del marco de referencia Ontoconcept con el formato de intercambio de reglas RIF

La presente investigación tiene como tema principal el estudio comparativo de las expresiones de RIF (formato de intercambio de reglas publicado por la W3C) con la capacidad expresiva del grafárbol ontológico, modelo conceptual propuesto dentro del framework Ontoconcept, que es una herramienta para la gestión del cambio ontológico, planteado en la tesis doctoral del ingeniero Julio César Chavarro Porras, bajo el título “Marco de referencia para la gestión del cambio en ontologías, basados en modelos conceptuales”. La motivación para la presente propuesta se fundamenta en la necesidad de establecer modelos conceptuales para la gestión de ontologías, continuando en una pequeña parte con el proceso de desarrollo de un sistema de administración de ontologías, consulta y razonamiento sobre diferentes ambientes, que es la finalidad a largo plazo de Ontoconcept. Este trabajo se encuentra vinculado a la línea de profundización de la maestría en ingeniería de sistemas y computación titulada Inteligencia Artificial, asociado al grupo de investigación GIA, grupo en el cual se vienen desarrollando diferentes proyectos de extensión del framework, así como generación de nuevas versione

Extensión del marco de referencia Ontoconcept con el formato de intercambio de reglas RIF

La presente investigación tiene como tema principal el estudio comparativo de las expresiones de RIF (formato de intercambio de reglas publicado por la W3C) con la capacidad expresiva del grafárbol ontológico, modelo conceptual propuesto dentro del framework Ontoconcept, que es una herramienta para la gestión del cambio ontológico, planteado en la tesis doctoral del ingeniero Julio César Chavarro Porras, bajo el título “Marco de referencia para la gestión del cambio en ontologías, basados en modelos conceptuales”. La motivación para la presente propuesta se fundamenta en la necesidad de establecer modelos conceptuales para la gestión de ontologías, continuando en una pequeña parte con el proceso de desarrollo de un sistema de administración de ontologías, consulta y razonamiento sobre diferentes ambientes, que es la finalidad a largo plazo de Ontoconcept. Este trabajo se encuentra vinculado a la línea de profundización de la maestría en ingeniería de sistemas y computación titulada Inteligencia Artificial, asociado al grupo de investigación GIA, grupo en el cual se vienen desarrollando diferentes proyectos de extensión del framework, así como generación de nuevas versione

Achieving Operational Service Line Efficiencies in a Cloud Computing Technology Vendor

This action research aims to understand the challenges faced by a cloud computing vendor in achieving operational efficiency for a specific service line and provides a practical framework that can be recommended for achieving operational efficiencies. The emergence of business problem, mainly in achieving sustainable performance, was apparent through the increase in costs, reduced revenues, and declining profit margins. The research provides insights into how the service line can address these challenges to enhance its performance. The study utilized a qualitative approach to data collection through semi-structured interviews with a sample of 12 stakeholders from the service line who have experience in service line strategy, execution processes, and defined performance indicators. The interviews were conducted with personnel from a UAE-based cloud computing technology vendor to explore and identify the challenges faced. Action research was carried out in three cycles to identify focus areas, determine future recommended actions, and plan for their execution. The cycles included the identification of expected challenges and the development of strategies to mitigate them. Thematic analysis was conducted to identify critical areas impacting performance and success indicators, such as revenue, costs, services-sales bookings, and financial margin. The findings were developed collaboratively and ethically to empower company participants. The study outcome outlines four focus areas to achieve operational efficiency in a service line: establishing foundations for success to cultivate a successful work culture, growing cloud service sales bookings and consumption, ensuring project delivery excellence, optimizing project cost and maintaining sustainability measures. Future recommended actions for each layer are detailed in the study. The study examined specified theoretical organizational concepts and disciplines. The findings propose a significant contribution in terms of the cloud computing service company and its organizational development by providing a practical execution framework for achieving service line operational efficiency, that can be implemented. The study emphasizes the importance of collaborative stakeholder engagement to generate knowledge. The framework provides cloud computing vendors with a practical tool for enhancing their service line operational efficiency which allows sustainable service line growth focused on crucial performance and success indicators

Recent Developments in Computational Collective Intelligence

VIII, 207 p. 90 illus.online resource