Martinez-Villaseñor, Lourdes
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Preferred name
Martinez-Villaseñor, Lourdes
Official Name
Martínez Villaseñor, María de Lourdes
Alternative Name
lmartine
Main Affiliation
ORCID
Scopus Author ID
55521085100
Researcher ID
N-7607-2018

Research Output
Now showing 1 - 10 of 15
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Publication

An ontology driven multi-agent system for client assignment in a bank queue

2010 , Martinez-Villaseñor, Lourdes , González-Marrón, David , González-Mendoza, Miguel , Hernández Gress, Neil

This paper presents an ontology driven multi-agent system that uses a negotiation process for decision support in a Bak Queue. The system assists queue client assignment based on the client profile and the cashiers’ workload in order to guarantee a minimum time response in client attention.

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Sharing and Reusing Context Information in Ubiquitous Computing Environments

2014 , Martinez-Villaseñor, Lourdes , González-Mendoza, Miguel

In highly dynamic environments it is not enough to model the user in order to provide proactive and personalized services. User features, preferences and needs change depending on different contextual aspects such as physical, social and computational conditions. Taking context into account in these environments implies coping with high openness and dynamicity of users and devices. Moreover, context modeling and context management is a complex task performed repeatedly in distributed environments, and users constantly share information about current activities, location, social events, goals, etc. In different applications. There is huge context information scattered over user's applications and devices that can be taken advantage of to provide more accurate adaptation and personalization. In this paper, we analyze the literature solutions with a focus on context information interoperability. We aim to identify basic requirements to perform the complex task of sharing and reusing context information between heterogeneous context providers and context consumers.

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Fuzzy aggregation of similarity values for electronic health record interoperability

2019 , Martinez-Villaseñor, Lourdes , Ponce, Hiram , González-Mendoza, Miguel

Schema matching is used for data integration, mediation, and conversion between heterogeneous sources. Nevertheless, mappings identified with an automatic or semi-automatic process can never be completely certain. In a process of concept alignment, it is necessary to manage uncertainty. In this paper, we present a fuzzy-based process of concept alignment for uncertainty management in schema matching problem. The ultimate goal is to enable interoperability between different electronic health records. Data integration of health information is done through the mediation of our ubiquitous user model framework. Results look promising and fuzzy theory proved to be a good fit for modeling uncertain schema matching. Fuzzy combined similarities can handle uncertainty in the schema matching process to enable interoperability between electronic health records improving the quality of mappings and diminishing the human error to verify the mappings. © 2019 - IOS Press and the authors. All rights reserved

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Special Issue on Interdisciplinary Artificial Intelligence: Methods and Applications of Nature-Inspired Computing

2022 , Ponce, Hiram , Martinez-Villaseñor, Lourdes , González-Mendoza, Miguel , Fonseca, Pablo A.

Inspiration in nature has been widely explored, from the macro to micro-scale. From a scientific perspective, these methods inspired by nature have proven to be efficient tools for tackling real-world problems because most of the latter are highly complex or the resources are limited to analyze them. This inspiration is justified by the fact that natural phenomena mainly emphasize adaptability, optimization, robustness, and organization, among other properties, to deal with complexity. In that sense, three methodologies are commonly considered: human-designed problem-solving techniques inspired by nature, the synthesis of natural phenomena to develop algorithms, and the use of nature-inspired materials to perform computations. Some applications of nature-inspired computing include data mining, machine learning, optimization, robotics, engineering control systems, human–machine interaction, healthcare, the Internet of Things, cloud computing, smart cities, and many others.|| This Special Issue aimed to cover original research works with emphasis on the methodologies and applications of nature-inspired computing to handle the above-mentioned complex systems. We received a total of 38 submitted papers, and 18 papers were accepted (covering 47% of acceptance rate).|| The Special Issue presents different works related to metaheuristic optimization methods and their applications of human brain inspiration and neural networks, natural language processing-based applications, and fuzzy-logic-based applications. ©2022 Applied Sciences, MDPI.

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Consumption of Profile Information from Heterogeneous Sources to Leverage Human-Computer Interaction

2013 , Martinez-Villaseñor, Lourdes , González-Mendoza, Miguel

Ubiquitous computing brings new challenges to system and application designers. It is not enough to deliver information at any time, at any place and in any form; information must be relevant to the user. Ubiquitous user model interoperability allows enrichment of adaptive systems obtaining a better understanding of the user, but conflict resolution is necessary to deliver the best suited values despite the existence of international standards for different concepts. In this paper, we present the algorithm of conflict resolution to consume of profile information from the ubiquitous user model. We illustrate the enrichment of user models with one elemental concept for human-computer interaction: the language concept.

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Overview of a Framework for Ubiquitous User Models Interoperability

2016 , Martinez-Villaseñor, Lourdes , González-Mendoza, Miguel

Researchers in the user modeling community have been interested in sharing and reuse profile information from heterogeneous sources. Ubiquitous user model interoperability allows enrichment of adaptive systems obtaining a better understanding of the user, and decreases the effort associated with creating a user model. We present a framework that enables the interoperability between profile suppliers and consumers with a mixed approach that consist in central ubiquitous user model ontology and a process of concept alignment. The central ontology is a flexible representation of a ubiquitous user model to cope with the dynamicity of a distributed multi-application environment that provides mediation between profile suppliers and consumers. The process of concept alignment automatically discovers the semantic mappings in order to interpret the information from heterogeneous sources and integrate them into a ubiquitous user model. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2017.

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Process of Concept Alignment for Interoperability between Heterogeneous Sources

2013 , Martinez-Villaseñor, Lourdes , González-Mendoza, Miguel

Some researchers in the community of user modeling envision the need to share and reuse information scattered over different user models of heterogeneous sources. In a multi-application environment each application and service must repeat the effort of building a user model to obtain just a narrow understanding of the user. Sharing and reusing information between models can prevent the user from repeated configurations, help deal with application and services’ “cold start” problem, and provide enrichment to user models to obtain a better understanding of the user. But gathering distributed user information from heterogeneous sources to achieve user models interoperability implies handling syntactic and semantic heterogeneity. In this paper, we present a process of concept alignment to automatically determine semantic mapping relations that enable the interoperability between heterogeneous profile suppliers and consumers, given the mediation of a central ubiquitous user model. We show that the process of concept alignment for interoperability based in a two-tier matching strategy can allow the interoperability between social networking applications, FOAF, Personal Health Records (PHR) and personal devices.

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Fuzzy-Based Approach of Concept Alignment

2017 , Martinez-Villaseñor, Lourdes , González-Mendoza, Miguel

The need to share and reuse information has grown in the new era of Internet of things and ubiquitous computing. Researchers in ontology and schema matching use mapping approaches in order to achieve interoperability between heterogeneous sources. The use of multiple similarity measures that take into account lexical, structural and semantic properties of the concepts is often found in schema matching for the purpose of data integration, sharing and reusing. Mappings identified by automatic or semi-automatic tools can never be certain. In this paper, we present a fuzzy-based approach to combine different similarity measures to deal with scenarios where ambiguity of terms hinder the process of alignment and add uncertainty to the match. © 2017, Springer International Publishing AG.

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An enhanced process of concept alignment for dealing with overweight and obesity

2013 , Martinez-Villaseñor, Lourdes , González-Mendoza, Miguel

A major challenge for creating personalized diet and activity applications is to capture static, semi-static and dynamic information about a person in a user-friendly way. Sharing and reusing information between heterogeneous sources like social networking applications, personal health records, specialized applications for diet and exercise monitoring, and personal devices with attached sensors can achieve a better understanding of the user. Gathering distributed user information from heterogeneous sources and making sense of it to enable user model interoperability entails handling the semantic heterogeneity of the user models. In this paper, we enhance the process of concept alignment to automatically determine semantic mapping relations to enable interoperability between heterogeneous health and fitting applications. We add an internal structure similarity measure to increase the quality of generated mappings of our previous work. We show that the addition of an internal structure analysis of source data in the process of concept alignment improves the efficiency and effectiveness of measuring results. Constrain and data type verification done in the internal structure analysis proved to be useful when dealing with common conflicts between concepts.

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Consumer Acceptance of an SMS-Assisted Smoking Cessation Intervention: A Multicountry Study

2013 , Martinez-Villaseñor, Lourdes , González-Mendoza, Miguel

A major challenge for creating personalized diet and activity applications is to capture static, semi-static and dynamic information about a person in a user-friendly way. Sharing and reusing information between heterogeneous sources like social networking applications, personal health records, specialized applications for diet and exercise monitoring, and personal devices with attached sensors can achieve a better understanding of the user. But gathering distributed user information from heterogeneous sources and making sense of it to enable user model interoperability entails handling the semantic heterogeneity of the user models. In this paper we describe a flexible user modeling ontology to provide representation for a ubiquitous user model and a process of concept alignment for interoperability between heterogeneous sources to address the lack of interoperability between profile suppliers and consumers. We provide an example of how information of different profile suppliers can be used to enrich fitness applications and personalize web services.

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