May 2019
Conference papers accepted
15/05/19/09:03 Filed in: Conference papers
J.M. Rodriguez-Jimenez and M. Ojeda-Aciego. Analysing patterns in false documents with Formal Concept Analysis to detect forgers. Intl Conference Computational and Mathematical Methods in Science and Engineering (CMMSE), Rota, 2019.
ABSTRACT Europe's system of open frontiers, commonly known as "Schengen", let people from different countries travel without problems crossing these frontiers. Different documents from these countries, not only European, could be found in road checkpoints, and Police forces have the problem that do not have an international database to know whether they are false or not. Some immigrants with legal problems in their original countries who need a new identity, or want a driver license to access to specific jobs, contact forgers who provide false documents with different levels of authenticity. Countries and Police Forces should improve their methodologies, by ensuring that staff is increasingly better able to detect false of falsified documents through their examination, and follow patterns to detect and ubícate these forgers. In this paper, we propose a method based on Formal Concept Analysis with negative attributes that allows Police forces analysing false documents, and provides a guide to enforce the detection of forgers.
I.P. Cabrera, P. Cordero, E. Muñoz-Velasco and M. Ojeda-Aciego. Relational Galois connections between fuzzy t-digraphs. Intl Conference Computational and Mathematical Methods in Science and Engineering (CMMSE), Rota, 2019.
ABSTRACT The notion of relational Galois connection is extended to be applied between fuzzy transitive directed graphs. In this framework, the components of the connection are crisp relations satisfying certain reasonable properties given in terms of the so-called full powering.
N. Madrid and M. Ojeda-Aciego. Towards a measure of inclusion from the index of inclusion between fuzzy sets. Intl Conference Computational and Mathematical Methods in Science and Engineering (CMMSE), Rota, 2019.
ABSTRACT Despite of the notion of inclusion between fuzzy sets has taken a great interest of a large number of researchers since Zadeh presented his seminal work in 1965, there is not a consensus about how to extend such a notion in fuzzy set theory yet. In this contribution we recall a recent fresh approach that represent the inclusion between two fuzzy sets by mean of a mapping (called index of inclusion) instead of a degree, as the standard approaches do. Moreover, we present a measure of inclusion (i.e. a degree) defined from our index of inclusion that allows to compare our approach directly with others in the literature.
D. López, A. Mora. Recommendations in CDSS using Fuzzy Formal Concept Analysis. Intl Conference Computational and Mathematical Methods in Science and Engineering (CMMSE), Rota, 2019.
ABSTRACT One of the hot topics in clinical research is hidden knowledge discovery in datasets with a high number of features (variables or attributes). We approach how to provide recommendations in Clinical Decision Support Systems (CDSS) to guide the experts in the diagnostic process. We work by mining graded implications from the dataset using the NEXTCLOSURE algorithm for Graded Attributes. Reasoning with these graded implications is done with the so-called Fuzzy Attribute Simplification Logic. As the number of graded implications mined from the fuzzy formal context is huge and with a high degree of redundancy, the objective is to obtain a equivalent set without redundancy, by applying the rules of the logic..
ABSTRACT Europe's system of open frontiers, commonly known as "Schengen", let people from different countries travel without problems crossing these frontiers. Different documents from these countries, not only European, could be found in road checkpoints, and Police forces have the problem that do not have an international database to know whether they are false or not. Some immigrants with legal problems in their original countries who need a new identity, or want a driver license to access to specific jobs, contact forgers who provide false documents with different levels of authenticity. Countries and Police Forces should improve their methodologies, by ensuring that staff is increasingly better able to detect false of falsified documents through their examination, and follow patterns to detect and ubícate these forgers. In this paper, we propose a method based on Formal Concept Analysis with negative attributes that allows Police forces analysing false documents, and provides a guide to enforce the detection of forgers.
I.P. Cabrera, P. Cordero, E. Muñoz-Velasco and M. Ojeda-Aciego. Relational Galois connections between fuzzy t-digraphs. Intl Conference Computational and Mathematical Methods in Science and Engineering (CMMSE), Rota, 2019.
ABSTRACT The notion of relational Galois connection is extended to be applied between fuzzy transitive directed graphs. In this framework, the components of the connection are crisp relations satisfying certain reasonable properties given in terms of the so-called full powering.
N. Madrid and M. Ojeda-Aciego. Towards a measure of inclusion from the index of inclusion between fuzzy sets. Intl Conference Computational and Mathematical Methods in Science and Engineering (CMMSE), Rota, 2019.
ABSTRACT Despite of the notion of inclusion between fuzzy sets has taken a great interest of a large number of researchers since Zadeh presented his seminal work in 1965, there is not a consensus about how to extend such a notion in fuzzy set theory yet. In this contribution we recall a recent fresh approach that represent the inclusion between two fuzzy sets by mean of a mapping (called index of inclusion) instead of a degree, as the standard approaches do. Moreover, we present a measure of inclusion (i.e. a degree) defined from our index of inclusion that allows to compare our approach directly with others in the literature.
D. López, A. Mora. Recommendations in CDSS using Fuzzy Formal Concept Analysis. Intl Conference Computational and Mathematical Methods in Science and Engineering (CMMSE), Rota, 2019.
ABSTRACT One of the hot topics in clinical research is hidden knowledge discovery in datasets with a high number of features (variables or attributes). We approach how to provide recommendations in Clinical Decision Support Systems (CDSS) to guide the experts in the diagnostic process. We work by mining graded implications from the dataset using the NEXTCLOSURE algorithm for Graded Attributes. Reasoning with these graded implications is done with the so-called Fuzzy Attribute Simplification Logic. As the number of graded implications mined from the fuzzy formal context is huge and with a high degree of redundancy, the objective is to obtain a equivalent set without redundancy, by applying the rules of the logic..