Lexicon-based sentiment analysis in texts using Formal Concept Analysis

In this paper, we present a novel approach for sentiment analysis that uses Formal Concept Analysis (FCA) to create dictionaries for classification. Unlike other methods that rely on pre-defined lexicons, our approach allows for the creation of customised dictionaries that are tailored to the specific data and tasks. By using a dataset of tweets categorised into positive and negative polarity, we show that our approach achieves a better performance than other standard dictionariesThis research is partially supported by the State Agency of Research (AEI), the Spanish Ministry of Science, Innovation, and Universities (MCIU), the European Social Fund (FEDER), the Junta de Andalucía (JA), and the Universidad de Málaga (UMA) through the FPU19/01467 (MCIU) internship and the research projects with reference PGC2018-095869-B-I00, TIN2017-89023-P, PID2021-127870OB-I00 (MCIU/AEI/FEDER, UE) and UMA18-FEDERJA-001 (JA/ UMA/ FEDER, UE). Funding for open access charge: Universidad de Málaga / CBU

A Study of Boolean Matrix Factorization Under Supervised Settings

International audienceBoolean matrix factorization is a generally accepted approach used in data analysis to explain data. It is commonly used under unsu-pervised setting or for data preprocessing under supervised settings. In this paper we study factors under supervised settings. We provide an experimental proof that factors are able to explain not only data as a whole but also classes in the data

Characterizing One-Sided Formal Concept Analysis by Multi-Adjoint Concept Lattices

Managing and extracting information from databases is one of the main goals in several fields, as in Formal Concept Analysis (FCA). One-sided concept lattices and multi-adjoint concept lattices are two frameworks in FCA that have been developed in parallel. This paper shows that one-sided concept lattices are particular cases of multi-adjoint concept lattices. As a first consequence of this characterization, a new attribute reduction mechanism has been introduced in the one-side framework.This research was partially supported by the 2014-2020 ERDF Operational Programme in collaboration with the State Research Agency (AEI) in Project PID2019-108991GB-I00 and with the Department of Economy, Knowledge, Business and University of the Regional Government of Andalusia in Project FEDER-UCA18-108612 and by the European Cooperation in Science & Technology (COST) Action CA17124

Efficient Axiomatization of OWL 2 EL Ontologies from Data by means of Formal Concept Analysis: (Extended Version)

We present an FCA-based axiomatization method that produces a complete EL TBox (the terminological part of an OWL 2 EL ontology) from a graph dataset in at most exponential time. We describe technical details that allow for efficient implementation as well as variations that dispense with the computation of extremely large axioms, thereby rendering the approach applicable albeit some completeness is lost. Moreover, we evaluate the prototype on real-world datasets.This is an extended version of an article accepted at AAAI 2024

Requirements Traceability: Recovering and Visualizing Traceability Links Between Requirements and Source Code of Object-oriented Software Systems

Requirements traceability is an important activity to reach an effective requirements management method in the requirements engineering. Requirement-to-Code Traceability Links (RtC-TLs) shape the relations between requirement and source code artifacts. RtC-TLs can assist engineers to know which parts of software code implement a specific requirement. In addition, these links can assist engineers to keep a correct mental model of software, and decreasing the risk of code quality degradation when requirements change with time mainly in large sized and complex software. However, manually recovering and preserving of these TLs puts an additional burden on engineers and is error-prone, tedious, and costly task. This paper introduces YamenTrace, an automatic approach and implementation to recover and visualize RtC-TLs in Object-Oriented software based on Latent Semantic Indexing (LSI) and Formal Concept Analysis (FCA). The originality of YamenTrace is that it exploits all code identifier names, comments, and relations in TLs recovery process. YamenTrace uses LSI to find textual similarity across software code and requirements. While FCA employs to cluster similar code and requirements together. Furthermore, YamenTrace gives a visualization of recovered TLs. To validate YamenTrace, it applied on three case studies. The findings of this evaluation prove the importance and performance of YamenTrace proposal as most of RtC-TLs were correctly recovered and visualized.Comment: 17 pages, 14 figure

Attribute Exploration of Gene Regulatory Processes

This thesis aims at the logical analysis of discrete processes, in particular of such generated by gene regulatory networks. States, transitions and operators from temporal logics are expressed in the language of Formal Concept Analysis. By the attribute exploration algorithm, an expert or a computer program is enabled to validate a minimal and complete set of implications, e.g. by comparison of predictions derived from literature with observed data. Here, these rules represent temporal dependencies within gene regulatory networks including coexpression of genes, reachability of states, invariants or possible causal relationships. This new approach is embedded into the theory of universal coalgebras, particularly automata, Kripke structures and Labelled Transition Systems. A comparison with the temporal expressivity of Description Logics is made. The main theoretical results concern the integration of background knowledge into the successive exploration of the defined data structures (formal contexts). Applying the method a Boolean network from literature modelling sporulation of Bacillus subtilis is examined. Finally, we developed an asynchronous Boolean network for extracellular matrix formation and destruction in the context of rheumatoid arthritis.Comment: 111 pages, 9 figures, file size 2.1 MB, PhD thesis University of Jena, Germany, Faculty of Mathematics and Computer Science, 2011. Online available at http://www.db-thueringen.de/servlets/DocumentServlet?id=1960

De la Información al Conocimiento. Aplicaciones basadas en implicaciones y computación paralela.

Sistemas de Recomendación Conversacionales Abordar la generación de recomendaciones haciendo uso de FCA es una aproximación existente en la literatura desde hace años. En esta tesis se ha abordado el problema de la dimensionalidad de SRs haciendo uso de conjuntos de implicaciones. Fecha de lectura de Tesis Doctoral: 29 Enero de 2019La gestión de la información es uno de los pilares esenciales de la Ingeniería Informática. Esta tesis doctoral toma como principal base teórica el Análisis Formal de Conceptos (FCA, por sus siglas en inglés: Formal Concept Analysis), y más concretamente, una de sus herramientas fundamentales: los conjuntos de implicaciones. La gestión inteligente de estos elementos mediante técnicas lógicas y computacionales confiere una alternativa para superar obstáculos en campos de la Ingeniería Informática como las bases de datos y los sistemas de recomendación (SRs). FCA parte de una representación de conjuntos de objetos y atributos por medio de tablas de datos. A partir de ahí, se generan dos herramientas básicas para representar el conocimiento: los retículos de conceptos y los conjuntos de implicaciones. Trabajar con implicaciones permite utilizar técnicas de razonamiento automático basadas en la lógica por medio de sistemas axiomáticos correctos y completos, como los axiomas de Armstrong y la Lógica de Simplificación. Estos métodos se utilizan en esta tesis doctoral sobre tres áreas de investigación: Claves Minimales Una clave de un esquema relacional está compuesta por un subconjunto de atributos que identifican a cada uno de los elementos de una relación. En concreto, se ha diseñado un nuevo método, denominado Closure Keys, que incorpora un mecanismo eficiente de poda de atributos e implicaciones mediante el método del Cierre de la Lógica de Simplificación. Generadores Minimales Se han estudiado, diseñado e implementado los métodos de generadores minimales referentes en la literatura y se ha hecho una clasificación de las ventajas e inconvenientes obtenidos por cada uno de ellos

FCAIR 2012 Formal Concept Analysis Meets Information Retrieval Workshop co-located with the 35th European Conference on Information Retrieval (ECIR 2013) March 24, 2013, Moscow, Russia

International audienceFormal Concept Analysis (FCA) is a mathematically well-founded theory aimed at data analysis and classifiation. The area came into being in the early 1980s and has since then spawned over 10000 scientific publications and a variety of practically deployed tools. FCA allows one to build from a data table with objects in rows and attributes in columns a taxonomic data structure called concept lattice, which can be used for many purposes, especially for Knowledge Discovery and Information Retrieval. The Formal Concept Analysis Meets Information Retrieval (FCAIR) workshop collocated with the 35th European Conference on Information Retrieval (ECIR 2013) was intended, on the one hand, to attract researchers from FCA community to a broad discussion of FCA-based research on information retrieval, and, on the other hand, to promote ideas, models, and methods of FCA in the community of Information Retrieval