Artículo
Permanent URI for this collectionhttps://hdl.handle.net/11285/345284
Artículo científico o editorial en una publicación periódica académica sujeto a revisión de pares. Cumple con los índices internacionales o bases de datos de amplia cobertura, como el listado del Current Contents, ISI WEB of Knowledge (http://isiknowledge.com/) e índice de revistas mexicanas de CONACYT (www.conacyt.mx/dac/revistas). Éstos indizan y resumen los artículos de revistas seleccionadas, en todas las áreas del saber.
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- Mapping relational databases through ontology matching: A case study on information migration(2011-10-24) Rodriguez-Mancha, Manuel; Cantu, Francisco J; Diaz-Prado, Aldo; Ceballos Cancino, Héctor GibránIn order to aid domain experts during data integration, several schema matching techniques have been proposed. Despite the facilities provided by these techniques, mappings between database schemas are still made manually. We propose a methodology for mapping two relational databases that uses ontology matching techniques and takes advantage of tools like D2R Server and AgreementMaker for automating mapping generation and for enabling unified access to information. We present the results obtained by some ontology matching algorithms in this context, demonstrating the feasibility of this approach.
- A multiagent knowledge and information network approach for managing research assets(ELSEVIER, 2010-07) Ceballos, Hector G; Cantu, Francisco J; Instituto Tecnológico y de Estudios Superiores de MonterreyWe describe a knowledge and information network approach for managing research assets in a knowledge-oriented organization using a multiagent system. The purpose of the approach is to provide decision makers a knowledge management framework to assist them in generating benefits from the knowledge assets developed by the research groups in a knowledge institution. The research assets under consideration are of three types: research products, intellectual capital and research programs. Research products include publications of various kinds, such as journal articles, research-based books, patents, technology licensing, trademarks, incubation of technology-based startup companies and others. Intellectual capital consists of the talent and expertise of research staff, such as professors, students and researchers. Research programs include academic curricula, research units, research infrastructure, and business incubators. The approach is supported by an intelligent platform that contains an information system, a multiagent-based system, a knowledge management system and a knowledge-information interpreter that coordinate repositories, domain ontologies and databases for handling the various types of research assets. The system provides a means for distributing existing research assets both within the organization and beyond, a variety of research reports, online consultations, a search engine, web services and data mining facilities for knowledge extraction. The knowledge and information generated by the system guide managers in defining strategies on competitiveness, for example, rankings, benchmarking, intellectual property and incubation of technology-based spin offs. The system has been operational at Tecnológico de Monterrey since August 2004, and has proved useful for both acquiring knowledge of research capabilities and for stimulating entrepreneurial science initiatives.
- Towards a causal framework for intelligent agents development(2009-11-13) Cantu, Francisco J; Ceballos Cansino, Héctor Gibrán; Instituto Tecnológico y de Estudios Superiores de MonterreyIn this paper we present a Causal Artificial Intelligence Design (CAID) theory that borrows notions from Classical philosophy for modeling intelligent agents. Principles introduced by this theory are used for extending a goal-driven BDI architecture and implementing what we call Causal Agent. This architecture incorporates causal formalisms like Pearl's Do calculus and C+ which are adapted to Semantic Web knowledge representations. Our approach includes an ontological agent description that enables and justifies the instantiation of agents as part of a plan. An experimental prototype used for validating experimentally our approach is commented.
- Modelling intelligent agents through causality theory(IEEE Computer Society, 2007-11-10) Cantu, Francisco J; Ceballos Cansino, Héctor Gibrán; Instituto Tecnológico y de Estudios Superiores de MonterreyWe introduce Causal Agents, a methodology and agent architecture for modeling intelligent agents based on Causality Theory. We draw upon concepts from classical philosophy about metaphysical causes of existing entities for defining agents in terms of their formal, material, efficient and final causes and use computational mechanisms from Bayesian causal models for designing causal agents. Agent's intentions, interactions and performance are governed by their final causes. A Semantic Bayesian Causal Model, which integrates a probabilistic causal model with a semantic layer, is used by agents for knowledge representation and inference. Agents are able to use semantic information from external stimuli (utterances, for example) which are mapped into the agent's causal model for reasoning about causal relationships with probabilistic methods. Our theory is being tested by an operational multiagents system implementation for managing research products.
- A knowledge-based information system for managing research programs and value creation in a university environment(2005-08-15) Cantu, Francisco J; Ceballos, Hector G; Mora, Silvia P; Escoffié, Miguel A; Instituto Tecnológico y de Estudios Superiores de MonterreyWe describe an integrated information system for managing knowledge generated from research and innovation activities in a university environment and for the creation of economic value from the resulting knowledge and innovations by using an action research methodology. The system uses a computer ontology for defining objects and provides both a corporate memory and a distribution vehicle for the knowledge and innovations invented by professors and graduate students. It comprises a set of interrelated subsystems that include scientific publications and innovations, graduate theses, professors, students, and research units. It generates statistics of research activities, a wide variety of reports and on line consultations as well as a search engine and data mining facilities for knowledge extraction. A version of the system has been operational for about a year and has been an important tool for creating wealth from the knowledge generated by the research activities.
- A knowledge-based entrepreneurial approach for business intelligence in strategic technologies: Bio-MEMS(2005-08-15) Cantu, Francisco J; Mora, Silvia P; Garcia, Aldo; Ceballos, Hector; Martinez, Sergio O; Instituto Tecnológico y de Estudios Superiores de MonterreyWe propose a knowledge-based entrepreneurial (KBE) approach for business intelligence in strategic technologies at industrial sectors. The KBE approach is at the convergence of business intelligence and knowledge management and is used for advising users in business decisions and potential risks. Our approach comprises both a technology roadmap model as well as a knowledge-based entrepreneurial portal for various technologies. We use the Biological-Micro-Electrical-and- Mechanical-Systems industry (Bio-MEMS) to illustrate the approach. The technology roadmap model identifies the main actors, defines their roles and specifies the issues to be addressed. It handles information about main products, market trends, companies, research centers, application domains, products, standardization, and intellectual properties issues. The portal provides knowledge about the main actors through automation facilities based on digital libraries, searching and knowledge extraction from databases, data-ware houses and the Web. We explain how the KBE is helping Bio-MEMS users in business analysis.