Hector G. Ceballos

Hector G. Ceballos
Tecnológico de Monterrey | ITESM · Campus Monterrey

PhD on Intelligent Systems
Director of the Living Lab & Data Hub of the Institute for the Future of Education (IFE) at Tecnologico de Monterrey.

About

70
Publications
9,940
Reads
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271
Citations
Citations since 2017
38 Research Items
203 Citations
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Additional affiliations
January 2013 - present
Tecnológico de Monterrey
Position
  • Autonomic Platforms through Probabilistic, Semantic and Causal Reasoning
Description
  • Causality, Bayesian Networks, Semantic Web, Autonomic Computing, Intelligent Organizations
August 2004 - present
Tecnologico de Monterrey
Position
  • ITESM's Research Corporate Memory
Description
  • Education

Publications

Publications (70)
Chapter
The scope of this research work is to integrate a statistical ontology model of scientometric indicators in a chatbot. Building a chatbot requires the use of Natural Language Processing (NLP) as a capability for recognizing users’ intent and extracting entities from users’ questions. We proposed a method for recognizing the requested indicator and...
Preprint
This study brings back the concept of weak-form efficiency in soccer betting markets. In sports, for odds to show efficiency as the ground truth of their price, they must reflect all historical information relevant to the match outcome probabilities. The aim is to show weak-form efficiency by dismissing closing odds on the winning probability model...
Article
Full-text available
High dropout rates and delayed completion in higher education are associated with considerable personal and social costs. In Latin America, 50% of students drop out, and only 50% of the remaining ones graduate on time. Therefore, there is an urgent need to identify students at risk and understand the main factors of dropping out. Together with the...
Article
Full-text available
The COVID-19 pandemic has changed our common habits and lifestyle. Occupancy information is valued more now due to the restrictions put in place to reduce the spread of the virus. Over the years, several authors have developed methods and algorithms to detect/estimate occupancy in enclosed spaces. Similarly, different types of sensors have been ins...
Article
Full-text available
Background This paper explores machine learning algorithms and approaches for predicting alum income to obtain insights on the strongest predictors and a ‘high’ earners’ class. Methods It examines the alum sample data obtained from a survey from a multicampus Mexican private university. Survey results include 17,898 and 12,275 observations before...
Article
Full-text available
Scientometrics is the field of study and evaluation of scientific measures such as the impact of research papers and academic journals. It is an important field because nowadays different rankings use key indicators for university rankings and universities themselves use them as Key Performance Indicators (KPI). The purpose of this work is to propo...
Article
Full-text available
The estimation of occupancy is a crucial contribution to achieve improvements in energy efficiency. The drawback of data or incomplete data related to occupancy in enclosed spaces makes it challenging to develop new models focused on estimating occupancy with high accuracy. Furthermore, considerable variation in the monitored spaces also makes it d...
Article
Full-text available
Clustering is an unsupervised learning technique used in data mining for finding groups with increased object similarity within but not between them. However, the absence of a-priori knowledge on the optimal clustering criterion, and the strong bias of traditional algorithms towards clusters with a specific shape, size, or density, raise the need f...
Conference Paper
Full-text available
The amount of information that social networks can shed on a certain topic is exponential compared to conventional methods. As new COVID-19 vaccines are approved by COFEPRIS in Mexico, society is acting differently by showing approval or rejection of some of these vaccines on social networks. Data analytics has opened the possibility to process, ex...
Preprint
Full-text available
Background: This paper explores different machine learning algorithms and approaches for predicting alum income to obtain insights on the strongest predictors for income and a ‘high’ earners’ class. Methods: The study examines the alum sample data obtained from a survey from Tecnologico de Monterrey, a multicampus Mexican private university, and an...
Article
Full-text available
Identifying strategies for researchers has been a problem investigated from different perspectives, such as choosing research topics or the effect of partner selection. Its importance lies in the effect these choices have in the long term and the importance of taking them into account at the beginning of the scientific career. This study aims to id...
Preprint
Full-text available
Scientometrics is the field of study and evaluation of scientific measures such as impact of research papers and academic journals. It is an important field because nowadays different rankings use key indicators for university rankings and universities themselves use them as Key Performance Indicators (KPI). The purpose of this work is to propose a...
Article
Full-text available
One of the main purposes of the countries’ economic expenditure in research is to achieve higher levels of scientific results which could impact in better living standards for society. Besides, research efficiency could be considered as a way of getting the largest number of scientific results with the minimum amount of financial investment. To ass...
Chapter
More than four out of 10 sports fans consider themselves soccer fans, making the game the world’s most popular sport. Sports are season based and constantly changing over time, as well, statistics vary according to the sport and league. Understanding sports communities in Social Networks and identifying fan’s expertise is a key indicator for soccer...
Article
Full-text available
To understand and approach the spread of the SARS-CoV-2 epidemic, machine learning offers fundamental tools. This study presents the use of machine learning techniques for projecting COVID-19 infections and deaths in Mexico. The research has three main objectives: first, to identify which function adjusts the best to the infected population growth...
Article
Full-text available
The impact of the strategies that researchers follow to publish or produce scientific content can have a long-term impact. Identifying which strategies are most influential in the future has been attracting increasing attention in the literature. In this study, we present a systematic review of recommendations of long-term strategies in research an...
Article
We present an approach for teaching data science to computer science and engineering students using a research-based learning pedagogy. This study is based on the results obtained teaching data science and data analytics graduate courses during 2020. The research-based learning pedagogy integrates project-based, problem-based, and cooperative based...
Article
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This research article presents a study to compare the teaching performance of teaching-only versus teaching-and-research professors at higher education institutions. It is a common belief that, generally, teaching professors outperform research professors in teaching-and-research universities according to student perceptions reflected in student su...
Article
Full-text available
The government of Mexico has done daily reports regarding COVID-19 (SARS-CoV-2) spreading status since the last days of February 2020, when the first cases of COVID-19 were confirmed in Mexico. In this daily conference, the Secretariat of Health also provides guidelines and policies for the public to follow to mitigate the virus' spreading. The sen...
Article
Full-text available
The understanding of occupancy patterns has been identified as a key contributor to achieve improvements in energy efficiency in buildings since occupancy information can benefit different systems, such as HVAC (Heating, Ventilation, and Air Conditioners), lighting, security, and emergency. This has meant that in the past decade, researchers have f...
Preprint
Full-text available
Background: To understand and approach the COVID-19 spread, Machine Learning offers fundamental tools. This study presents the use of machine learning techniques for the projection of COVID-19 infections and deaths in Mexico. The research has three main objectives: first, to identify which function adjusts the best to the infected population growth...
Article
Full-text available
Hyper-heuristics aim at interchanging different solvers while solving a problem. The idea is to determine the best approach for solving a problem at its current state. This way, every time we make a move it gets us closer to a solution. The problem changes; so does its state. As a consequence, for the next move, a different solver may be invoked. H...
Conference Paper
In Mexico, higher education is constantly suffering from low percentage of placement and interest of individuals for a graduate degree. Mexico needs more postgraduate students to increase the research and development activities and boost innovation in the private sector, especially in strategic industries. This paper suggests the use of data mining...
Chapter
Full-text available
El Tecnológico de Monterrey cuenta con dos plataformas para la gestión y la difusión del conocimiento científico, las cuales son el Sistema de Información de Investigación Actual (Current Research Information System – CRIS) para la gestión institucional interna y el Repositorio Institucional (RI) desarrollado como parte del movimiento educativo abi...
Preprint
Full-text available
The main purpose of the economic expenditure of countries in research and development is to achieve higher levels of scientific findings within research ecosystems, which in turn could generate better living standards for society. Therefore, the collection of scientific production constitutes a faithful image of the capacity, trajectory and scienti...
Conference Paper
"Semantic Web Technology proposes the use of linked data and ontologies as a mean for providing meaning to information. Even though several tools for the analysis and visualization of linked data exist, these tools require a lot of specialized knowledge to fulfill a purpose. Additionally, this complexity hardens its use for nonexperienced users the...
Article
Data Envelopment Analysis (DEA) is a methodology for evaluating the relative efficiencies of a set of decision-making units (DMUs), based on their multiple inputs and outputs. The original model is based on the assumption that DMUs operate independently of one another. However, this assumption may not apply in some situations, as in the case we pre...
Article
The factors that foster successful scientific collaboration and teamwork have been studied extensively. However, these factors have been studied in isolation and it is not clear to what extent one factor is more relevant than other in the formation of research groups. In this work we propose a new methodology based on network analysis to simultaneo...
Chapter
Full-text available
In the context of the Open Access movement, repositories provide a window for scientific and academic communities to preserve and share knowledge. Glassman & Kang (2016) stress the importance of educational institutions developing technologies that support an open educational system. Accordingly, Ramírez (2015) mentions that open access is an oppor...
Article
Full-text available
A case study for impelling university research productivity and impact through collaboration is presented. Scientometric results support the hypothesis that a knowledge management model increased research collaboration and thereby boosted a university’s number of publications and citations. Results come from fifteen years of data at a Mexican unive...
Conference Paper
Full-text available
La actualización constante de un Repositorio Institucional (RI) es una de las estrategias para incrementar la visibilidad de los recursos educativos y la producción científica de forma abierta. En el presente estudio los procesos de investigación se condujeron para responder a la interrogante ¿Cuáles son las ventajas y desventajas de integrar una H...
Chapter
Agent-based technologies, originally proposed with the aim of assisting human activities, have been recently adopted in industry for automating business processes. Business Process Model and Notation (BPMN) is a standard notation for modeling business processes, that provides a rich graphical representation that can be used for common understanding...
Conference Paper
Full-text available
Availability of eGovernment open data is blooming in Mex-ico motivated by the recent publication of the Open Data Act. Mexican government agencies are publishing open data of different kind in standard formats such as spreadsheets and maps. Nevertheless, datasets published in portals (e.g. datos.gob.mx) lack of annotations for identifying connectio...
Conference Paper
Full-text available
Agent-based technologies, originally proposed with the aim of assisting human activities, have been recently adopted in industry for automating business processes. Business Process Model and Notation (BPMN) is a standard notation for modeling business processes that provides a rich graphical representation that can be used for common understanding...
Conference Paper
Full-text available
Agent-based technologies, originally proposed with the aim of assisting human activities, have been recently adopted in industry for automating business processes. Business Process Model and Notation (BPMN) is a standard notation for modeling business processes, that provides a rich graphical representation that can be used for common understanding...
Conference Paper
Full-text available
Entity matching is a problem that concerns many data management processes. If we consider matching between entities represented by RDF individuals we might find attributes values lists with variable-length for some properties, which will lead us to the problem of comparing multi-valued attributes, e.g. comparing author names lists for determining p...
Article
Full-text available
Information integration is not a trivial activity. Information managers face problems like: heterogeneity (in data, schemas, syntax and platforms), distribution and duplicity. In this paper we: 1) analyze ontology-based methodologies that provide mediation frameworks for integrating and reconciling information from structured data sources, and 2) p...
Data
Full-text available
In this paper, we propose to use the Activity Theory and causal diagrams for modelling human activities with the aim of facilitating the speci�cation of an agent-based assistance system through the Prometheus methodology. As a case study, we consider the elder medication activity, a recurring, complex and context-rich activity that involves several...
Conference Paper
Full-text available
For improving research productivity, quality and dissemination, we propose the development of a visual recommendation tool summing up scientific collaboration best-practices found in literature. Social Network Analysis are applied to a coauthorship network for generating a Potential Collaboration Index (PCI) based on productivity, connectivity, sim...
Conference Paper
In this paper, we propose to use the Activity Theory and causal diagrams for modelling human activities with the aim of facilitating the specification of an agent-based assistance system through the Prometheus methodology. As a case study, we consider the elder medication activity, a recurring, complex and context-rich activity that involves severa...
Chapter
Full-text available
In this chapter we address the importance of inner collaboration and social networking within an institution to better achieve their goals and objectives and present a model and experience in fostering inner collaboration and networking among research groups from multiple disciplines in a university environment
Thesis
Full-text available
The current competitive environment motivated Knowledge Management (KM) theorists to propose the notion of Organizational Intelligence (OI) for enabling a rapid response of large organizations to changing conditions. KM practitioners consider that OI resides in both processes and members of the organization, and recommend implementing learning mech...
Article
Full-text available
We 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 knowled...
Conference Paper
Full-text available
In Electronic Institutions [1], agents may be prevented from achieving their goals if other participants are not present in a given scene. In order to overcome this situation we propose the addition of an institutional agent in charge of dispatch-ing agents to scenes through a participation request proto-col. We further propose to endow this agent...
Conference Paper
Full-text available
The Electronic Institutions (EIs) framework is designed for regulating interactions among heterogeneous agents in open systems [1]. In EIs, agent interactions are speech acts whose exchange is organized as conversation protocols called scenes. Agents can participate simultaneously in multiple scenes playing a single role in each one of them. Howeve...
Conference Paper
Full-text available
In 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 Pe...
Article
Full-text available
This report presents the development of an Electronic Institution for auditing information in a research and graduate programs corporate memory. Electronic Institutions are used for formalizing processes performed by human experts and professors providing a platform for gradual automation. New features like a Directory Facilitator and a protocol fo...
Article
Full-text available
We 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 c...
Article
Full-text available
A medida que el conocimiento Ontológico cobra más importancia en sistemas basados en agentes, su manejo se vuelve crucial para aplicaciones exitosas. Pero colocar to- das las capacidades para el manejo de ontologías en cada uno de los agentes del sistema puede volverlo demasiado pesado. Proponemos un enfoque híbrido en el cual parte de la ontología...
Article
As Ontologic knowledge gets more and more impor- tant in agent-based systems, its handling becomes cru- cial for successful applications. We propose a hybrid approach, in which part of the ontology is handled locally, using a "client component", and the rest of the ontological knowledge is handled by an "ontology agent", which is accessed by the ot...
Conference Paper
Full-text available
We 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 co...
Conference Paper
Full-text available
As Ontologic knowledge gets more and more important in agent-based systems, its handling becomes crucial for successful appli- cations. In the context of agent-based applications, we propose a hybrid approach, in which part of the ontology is handled locally, using a "client component", and the rest of the ontological knowledge is handled by an "on...
Conference Paper
Full-text available
As ontologic knowledge gets more and more important in agent-based systems, its handling becomes crucial for successful applications. We propose a hybrid approach, in which part of the ontology is handled locally, using a "client component", and the rest of the ontological knowledge is handled by an "ontology agent", which is accessed by the other...